From the uDemy course on LLM engineering.
https://www.udemy.com/course/llm-engineering-master-ai-and-large-language-models
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4200 lines
502 KiB
4200 lines
502 KiB
{ |
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"cells": [ |
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{ |
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"cell_type": "markdown", |
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"id": "dfe37963-1af6-44fc-a841-8e462443f5e6", |
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"metadata": {}, |
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"source": [ |
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"## Udemy Video Subtitle Vectorization (Expert on LLM engineering) \n", |
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"\n", |
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"This project will uses subtitle files from Ed Donners excellent LLM engineering course on Udemy.\n", |
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"\n", |
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"These can be downloaded using the following process:\n", |
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"- Useing an android phone, download Udemy app and open the LLM engineering course. \n", |
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"- There is option to download the videos as single files or section wise. \n", |
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"- Download them and along with those videos subs or cc are also downloaded as .srt’s.\n", |
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"- Plug in your laptop to the android phone using USB and select file transfer in the notification.\n", |
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"- Open a file explorer and copy the subtitle files (srt format)\n", |
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"- Here’s the location of subs in android \"internal storage/android/data/com.udemy.android/files/udemy-subtitle-downloads\"\n", |
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"\n", |
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"the raw srt files are stored in the folder \"subtitles/srts\". The code below will use the langchain textloader but will preprocess the srt files to remove the timestamps.\n", |
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"\n", |
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"### Note: this is only for educational and testing purposes and you should contact Ed Donnner to seek his permission if you want to use the subtitles." |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": 62, |
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"id": "ba2779af-84ef-4227-9e9e-6eaf0df87e77", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"# imports\n", |
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"\n", |
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"import os\n", |
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"import glob\n", |
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"from dotenv import load_dotenv\n", |
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"import gradio as gr" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": 61, |
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"id": "802137aa-8a74-45e0-a487-d1974927d7ca", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"# imports for langchain and Chroma and plotly\n", |
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"\n", |
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"from langchain.document_loaders import DirectoryLoader, TextLoader\n", |
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"from langchain.text_splitter import CharacterTextSplitter\n", |
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"from langchain.schema import Document\n", |
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"from langchain_openai import OpenAIEmbeddings, ChatOpenAI\n", |
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"from langchain_chroma import Chroma\n", |
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"import numpy as np\n", |
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"from sklearn.manifold import TSNE\n", |
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"import plotly.graph_objects as go\n", |
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"import re" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": 41, |
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"id": "58c85082-e417-4708-9efe-81a5d55d1424", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"# price is a factor for our company, so we're going to use a low cost model\n", |
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"\n", |
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"MODEL = \"gpt-4o-mini\"\n", |
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"db_name = \"vector_db\"" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": 42, |
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"id": "ee78efcb-60fe-449e-a944-40bab26261af", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"# Load environment variables in a file called .env\n", |
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"\n", |
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"load_dotenv()\n", |
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"os.environ['OPENAI_API_KEY'] = os.getenv('OPENAI_API_KEY', 'your-key-if-not-using-env')" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": 43, |
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"id": "730711a9-6ffe-4eee-8f48-d6cfb7314905", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"# Read in documents using LangChain's loaders\n", |
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"# Take everything in all the sub-folders of our knowledgebase\n", |
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"\n", |
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"folders = glob.glob(\"subtitles/srts/*\")\n", |
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"\n", |
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"# With thanks to CG and Jon R, students on the course, for this fix needed for some users \n", |
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"text_loader_kwargs = {'encoding': 'utf-8'}\n", |
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"# If that doesn't work, some Windows users might need to uncomment the next line instead\n", |
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"# text_loader_kwargs={'autodetect_encoding': True}\n", |
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"\n", |
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"def preprocess_srt_content(content):\n", |
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" \"\"\"\n", |
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" Preprocess the content of an SRT file to remove timing information and the WEBVTT header.\n", |
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" \"\"\"\n", |
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" # Remove the WEBVTT header\n", |
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" content = re.sub(r'^WEBVTT\\s*', '', content, flags=re.IGNORECASE)\n", |
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" # Remove timing lines (e.g., 00:00.680 --> 00:08.540)\n", |
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" content = re.sub(r'\\d{2}:\\d{2}\\.\\d{3} --> \\d{2}:\\d{2}\\.\\d{3}', '', content)\n", |
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" # Remove extra newlines and strip leading/trailing whitespace\n", |
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" return \"\\n\".join(line.strip() for line in content.splitlines() if line.strip())\n", |
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"\n", |
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"documents = []\n", |
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"for folder in folders:\n", |
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" video_number = os.path.basename(folder)\n", |
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" loader = DirectoryLoader(folder, glob=\"**/en_US.srt\", loader_cls=TextLoader)\n", |
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" folder_docs = loader.load()\n", |
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"\n", |
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" for doc in folder_docs:\n", |
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" # Preprocess the document content\n", |
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" cleaned_content = preprocess_srt_content(doc.page_content)\n", |
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" # Replace the original content with the cleaned content\n", |
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" doc.page_content = cleaned_content\n", |
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" # Add metadata\n", |
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" doc.metadata[\"video_number\"] = video_number\n", |
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" documents.append(doc)\n" |
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] |
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}, |
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{ |
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"cell_type": "markdown", |
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"id": "f065d4b1-80b7-4e15-abd4-60a83e752ea8", |
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"metadata": {}, |
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"source": [ |
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"# Please note:\n", |
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"\n", |
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"In the next cell, we split the text into chunks.\n", |
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"\n", |
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"If you have problems, you can try to fix them by changing the chunk_size from 1,000 to 2,000 and the chunk_overlap from 200 to 400. \n", |
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"This shouldn't be required; but if it happens to you, please make that change! \n", |
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"(Note that LangChain may give a warning about a chunk being larger than 1,000 - this can be safely ignored)." |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": 44, |
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"id": "7310c9c8-03c1-4efc-a104-5e89aec6db1a", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=200)\n", |
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"chunks = text_splitter.split_documents(documents)" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": 45, |
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"id": "cd06e02f-6d9b-44cc-a43d-e1faa8acc7bb", |
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"metadata": {}, |
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"outputs": [ |
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{ |
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"data": { |
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"text/plain": [ |
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"217" |
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] |
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}, |
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"execution_count": 45, |
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"metadata": {}, |
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"output_type": "execute_result" |
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} |
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], |
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"source": [ |
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"len(chunks)" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": 46, |
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"id": "2c54b4b6-06da-463d-bee7-4dd456c2b887", |
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"metadata": {}, |
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"outputs": [ |
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{ |
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"name": "stdout", |
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"output_type": "stream", |
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"text": [ |
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"Video numbers found: 60616407, 59170043, 59507329, 59505329, 60614541, 59471979, 59166453, 59295587, 59295545, 59670259, 59166421, 59295493, 59166461, 59166919, 60616845, 59472873, 59668027, 59472017, 59668181, 60614589, 59473021, 59166443, 59507017, 60619721, 59170055, 59665129, 59295439, 59673721, 59472441, 59507423, 59473201, 59472011, 59671567, 60616927, 59170297, 59667365, 60620395, 59295599, 59669375, 59507435, 59297749, 59297599, 59297603, 59472491, 59297595, 60616663, 59170165, 59472383, 59506713, 59297561, 60620397, 59166951, 59472503, 59295609, 59670933, 59170291, 59295429, 59473071, 59472027, 59166949, 60616629, 60619227, 59297733, 59669211, 59473191, 59667829, 59295423, 59170037, 59170025, 59170227, 59671231, 59673449, 59503703, 59669631, 59166353, 59671441, 59673663, 59668923, 60619619, 59170255, 59508289, 59507785, 60619299, 60619501, 60616623, 59473147, 59170135, 59473089, 59295435, 59472425, 59295579, 59669389, 60617259, 59673639, 59508297, 60619247, 60619289, 59472137, 59669049, 59472693, 60620143, 59295363, 59503705, 59167009, 59508175, 59669217, 59166915, 59295441, 59508055, 59667841, 59472421, 60619123, 59297721, 59508057, 59297601, 59297735, 59670369, 59170223, 59271655, 59297773, 59170057, 59504785, 59473159, 59166281, 60617251, 59295459, 59472413, 59665127, 59295619, 59670121, 59666831, 60619447, 59670171, 60616493, 59473101, 59473019, 59666211, 59671315, 60619439, 59295451, 59297723, 59673431, 59169991, 59472333, 60619149, 59295607, 60619281, 59297575, 59472429, 60619883, 59670073, 59167007, 59671221, 59295553, 59166981, 60595637, 59170235, 59297593, 60614591, 59504887, 60616895, 59166947, 60620025, 60617163, 60622463, 59506611, 59166481, 59472505, 59295431, 59472463, 59167015, 59170233, 60395261, 59508121, 59166847, 60620169, 60616423, 59473137, 59170107, 59297743, 59506507, 59472883, 59295541, 59507489, 60619577, 59507687, 59506929, 59170093, 59166465, 59166317, 59295601, 59509185, 60619651, 59169985, 59505337, 59295527, 59667357, 59673595, 59295549, 59297693, 60620375, 59297585, 59670087, 59472067, 59295583, 60616855, 59295377, 60619275, 59504769, 59507635, 60616833, 59297609, 60619429, 59472307, 59507313, 60617255, 59472007\n" |
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] |
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} |
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], |
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"source": [ |
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"video_numbers = set(chunk.metadata['video_number'] for chunk in chunks)\n", |
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"print(f\"Video numbers found: {', '.join(video_numbers)}\")" |
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] |
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}, |
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{ |
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"cell_type": "markdown", |
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"id": "77f7d2a6-ccfa-425b-a1c3-5e55b23bd013", |
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"metadata": {}, |
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"source": [ |
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"## A sidenote on Embeddings, and \"Auto-Encoding LLMs\"\n", |
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"\n", |
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"We will be mapping each chunk of text into a Vector that represents the meaning of the text, known as an embedding.\n", |
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"\n", |
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"OpenAI offers a model to do this, which we will use by calling their API with some LangChain code.\n", |
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"\n", |
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"This model is an example of an \"Auto-Encoding LLM\" which generates an output given a complete input.\n", |
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"It's different to all the other LLMs we've discussed today, which are known as \"Auto-Regressive LLMs\", and generate future tokens based only on past context.\n", |
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"\n", |
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"Another example of an Auto-Encoding LLMs is BERT from Google. In addition to embedding, Auto-encoding LLMs are often used for classification.\n", |
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"\n", |
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"### Sidenote\n", |
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"\n", |
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"In week 8 we will return to RAG and vector embeddings, and we will use an open-source vector encoder so that the data never leaves our computer - that's an important consideration when building enterprise systems and the data needs to remain internal." |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": 47, |
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"id": "78998399-ac17-4e28-b15f-0b5f51e6ee23", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"# Put the chunks of data into a Vector Store that associates a Vector Embedding with each chunk\n", |
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"\n", |
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"embeddings = OpenAIEmbeddings()\n", |
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"\n", |
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"# If you would rather use the free Vector Embeddings from HuggingFace sentence-transformers\n", |
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"# Then replace embeddings = OpenAIEmbeddings()\n", |
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"# with:\n", |
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"# from langchain.embeddings import HuggingFaceEmbeddings\n", |
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"# embeddings = HuggingFaceEmbeddings(model_name=\"sentence-transformers/all-MiniLM-L6-v2\")" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": 48, |
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"id": "763e51ff-5787-4a56-8176-36b7c5796fe3", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"# Check if a Chroma Datastore already exists - if so, delete the collection to start from scratch\n", |
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"\n", |
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"if os.path.exists(db_name):\n", |
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" Chroma(persist_directory=db_name, embedding_function=embeddings).delete_collection()" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": 49, |
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"id": "99fe3a37-480f-4d55-be48-120588d5846b", |
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"metadata": {}, |
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"outputs": [ |
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{ |
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"name": "stdout", |
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"output_type": "stream", |
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"text": [ |
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"Vectorstore created with 217 documents\n" |
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] |
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} |
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], |
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"source": [ |
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"# Create our Chroma vectorstore!\n", |
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"\n", |
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"vectorstore = Chroma.from_documents(documents=chunks, embedding=embeddings, persist_directory=db_name)\n", |
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"print(f\"Vectorstore created with {vectorstore._collection.count()} documents\")" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": 50, |
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"id": "057868f6-51a6-4087-94d1-380145821550", |
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"metadata": {}, |
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"outputs": [ |
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{ |
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"name": "stdout", |
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"output_type": "stream", |
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"text": [ |
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"The vectors have 1,536 dimensions\n" |
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] |
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} |
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], |
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"source": [ |
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"# Get one vector and find how many dimensions it has\n", |
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"\n", |
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"collection = vectorstore._collection\n", |
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"sample_embedding = collection.get(limit=1, include=[\"embeddings\"])[\"embeddings\"][0]\n", |
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"dimensions = len(sample_embedding)\n", |
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"print(f\"The vectors have {dimensions:,} dimensions\")" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"id": "61e393a0-dd4c-419f-842f-60c1cb3b716b", |
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"metadata": {}, |
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"outputs": [], |
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"source": [] |
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}, |
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{ |
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"cell_type": "markdown", |
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"id": "b0d45462-a818-441c-b010-b85b32bcf618", |
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"metadata": {}, |
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"source": [ |
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"## Visualizing the Vector Store\n", |
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"\n", |
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"Let's take a minute to look at the documents and their embedding vectors to see what's going on." |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": 51, |
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"id": "cfb855dc-1610-4aaf-8e5f-68c26ce640a5", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"# Convert the video numbers into unique colors that we can visualize\n", |
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"import hashlib\n", |
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"\n", |
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"def video_numbers_to_hex_colors(video_numbers):\n", |
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" return [f\"#{hashlib.sha256(v.encode()).hexdigest()[:6]}\" for v in video_numbers]\n", |
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"\n" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": 58, |
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"id": "b98adf5e-d464-4bd2-9bdf-bc5b6770263b", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"# Prework\n", |
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"\n", |
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"result = collection.get(include=['embeddings', 'documents', 'metadatas'])\n", |
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"vectors = np.array(result['embeddings'])\n", |
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"documents = result['documents']\n", |
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"video_numbers = [metadata['video_number'] for metadata in result['metadatas']]\n", |
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"colors = video_numbers_to_hex_colors(strings)\n", |
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"\n" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": 55, |
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"id": "427149d5-e5d8-4abd-bb6f-7ef0333cca21", |
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"metadata": {}, |
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"outputs": [ |
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{ |
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"data": { |
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"application/vnd.plotly.v1+json": { |
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"config": { |
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"plotlyServerURL": "https://plot.ly" |
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}, |
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"data": [ |
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{ |
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"hoverinfo": "text", |
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"marker": { |
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"Video: 59506507<br>Text: Well, I realized that was a whole lot of theory, but I hope it gave you a good intuition that will\nb...", |
|
"Video: 59671315<br>Text: Okay, so here we are, back in Jupyter Lab, ready for the next use of a frontier model, and see this\n...", |
|
"Video: 60616895<br>Text: It feels like 100 videos ago that I told you that we were going to have instant gratification with o...", |
|
"Video: 60619275<br>Text: And we will conclude our expedition into the world of frontier models through their chat interface b...", |
|
"Video: 59472693<br>Text: Friends.\nI am absolutely exhausted.\nI am exhausted and a little tiny bit traumatized.\nAnd you are so...", |
|
"Video: 59670121<br>Text: So it's business time right now.\nWe are going to build a Rag pipeline to estimate the price of produ...", |
|
"Video: 59295619<br>Text: Welcome back to the the moment when we bring it all together into a beautiful user interface.\nBut fi...", |
|
"Video: 60617163<br>Text: And already that wraps up day two.\nNow that you have built that solution.\nAnd congratulations on tha...", |
|
"Video: 60616423<br>Text: So I hope you've just enjoyed yourself experimenting with different LMS locally on your box using th...", |
|
"Video: 59170227<br>Text: Welcome back to Google Colab.\nHere we are ready to explore the wonderful world of Tokenizers.\nSo, uh...", |
|
"Video: 59169985<br>Text: So I hope you enjoyed that whirlwind tour of Google Colab.\nHere's just a little screenshot example o...", |
|
"Video: 60616927<br>Text: It's time for our first LM experiment at this point.\nSo some of this you may know well, you may know...", |
|
"Video: 59673721<br>Text: And here we are in JupyterLab for the last time, and we are looking here at day five, the last day\no...", |
|
"Video: 59508055<br>Text: I'm so very happy that you've reached this epic moment in the course and that you're hanging in ther...", |
|
"Video: 59670259<br>Text: It's remarkable.\nBut you are now at the 95% point.\nThere's 5% remaining of this course.\nUh, maybe it...", |
|
"Video: 60616623<br>Text: So we're now going to start week one of the course when we are going to be looking at exploring fron...", |
|
"Video: 59472383<br>Text: And welcome back to the week six folder.\nWe're now at day two, which is the second and final stage o...", |
|
"Video: 59670171<br>Text: So as the very final step on this part four of day two of week eight, we are now going to build an\ne...", |
|
"Video: 59297721<br>Text: And so now the time has come to talk about the most crucial aspect of Rag, which is the idea of vect...", |
|
"Video: 59297599<br>Text: Well, that was a sneaky detour I took you on in the last one.\nI hope you enjoyed it though, and I ho...", |
|
"Video: 59507635<br>Text: Look, I hope you're excited.\nYou really should be.\nYou've been through 80% of the course and it's al...", |
|
"Video: 59669375<br>Text: Here we are for the day.\n2.1 notebook.\nAnd don't let it be said that I don't ever do anything for yo...", |
|
"Video: 59297733<br>Text: Welcome back to JupyterLab and welcome to your first experiment with the world of Long Chain.\nLet me...", |
|
"Video: 59670369<br>Text: It is terrific that you're hanging on in there and making such great progress with this course.\nAs w...", |
|
"Video: 59166281<br>Text: And with that, amazingly, you completed day one of week two already and that gets you to the 15% poi...", |
|
"Video: 59671567<br>Text: Well, the first thing you're going to notice is that I don't have a notebook open for you.\nAnd that'...", |
|
"Video: 59297593<br>Text: And welcome to continuing our journey with Hrag.\nAnd today it's time to unveil Liang Chen.\nSo first,...", |
|
"Video: 59166461<br>Text: And welcome back to the lab.\nHere we are in Jupyter Lab and we are going to go into week two.\nAnd we...", |
|
"Video: 59167007<br>Text: Well, how fabulous is that?\nI hope that you are as wowed as I am by our new airline, I assistant and...", |
|
"Video: 59508121<br>Text: The moment has arrived.\nHere we go.\nWe're in fine tuning.\nWe do fine tuning.\nTrain.\nThere is also a ...", |
|
"Video: 59295579<br>Text: All right.\nAre you excited to see how this goes?\nLet's give it a try.\nSo in this next section, I cre...", |
|
"Video: 60620375<br>Text: And with that, we've reached an important milestone.\nThe first week of our eight week journey is com...", |
|
"Video: 59472491<br>Text: Welcome back.\nIf you are following along with me in JupyterLab, as I hope you are, then you will nee...", |
|
"Video: 59472425<br>Text: Welcome to week six, day three.\nToday is going to be a day that you will either love or you will hat...", |
|
"Video: 59508057<br>Text: Actually slight change in plan.\nI'm going to wrap up the day.\nDay three at this point, and say that ...", |
|
"Video: 60619577<br>Text: And for the final piece of background information, I wanted to take another moment to talk about API...", |
|
"Video: 59170291<br>Text: Welcome back to Colab and welcome back to our business project.\nSo again our assignment, we are due ...", |
|
"Video: 60619651<br>Text: I mentioned before an AI company called vellum.\nWhen we were talking about the different questions, ...", |
|
"Video: 59473191<br>Text: And you thought we'd never get here.\nHere we are in Jupyter Lab, running our fine tuning for a front...", |
|
"Video: 59170297<br>Text: And here we are in Google Colab, ready for fun with models.\nSo first we do the usual Pip installs an...", |
|
"Video: 59167015<br>Text: Welcome back to Jupyter Lab and welcome to Day Five's Lab.\nAnd this is going to be lots of creativit...", |
|
"Video: 59170043<br>Text: Let me enthusiastically welcome you all back to week three of our LLM engineering journey.\nIf you en...", |
|
"Video: 59473147<br>Text: Well, I'm very relieved.\nI've got that behind me.\nNo more human testing for me.\nWe'll have one final...", |
|
"Video: 59166453<br>Text: Welcome back and welcome to our continuing JupyterLab experience.\nUh, I'm hopefully going to keep yo...", |
|
"Video: 59166915<br>Text: Welcome back to the wonderful world of JupyterLab.\nAnd here we are in week two.\nDay three.\nUh, bring...", |
|
"Video: 59667365<br>Text: Here we are back in Colab, looking at the week seven, day five of the Colab notebooks and I'm on a\nT...", |
|
"Video: 60616845<br>Text: We're on the home stretch.\nThis is the final step in the environment setup, and it's an easy one.\nIt...", |
|
"Video: 59295459<br>Text: And welcome back to More Leaderboard Fest as we go through some more leaderboards.\nBut this time we'...", |
|
"Video: 59471979<br>Text: So we now turn to the parts of the problem, which is perhaps, let's say, not as glamorous as some\nof...", |
|
"Video: 59503705<br>Text: And so now we talk about quantization the q and q Laura.\nQ stands for quantized quantized.\nLaura.\nAn...", |
|
"Video: 59472505<br>Text: So the good news is that this is the very final video about data set curation.\nYou were probably fed...", |
|
"Video: 59669217<br>Text: And welcome to the next part of visualizing the data.\nAnd just very quickly to show it to you in 3D....", |
|
"Video: 59671221<br>Text: I gotta tell you, I don't like to toot my horn a whole lot, but I do think that I've done a great\njo...", |
|
"Video: 59503703<br>Text: Well.\nHello there everybody.\nI am so grateful that you've made it through to the start of week seven...", |
|
"Video: 59473201<br>Text: Well, before we do a postmortem on what happened, let's just quickly look at the standing the rankin...", |
|
"Video: 60622463<br>Text: In this video, we're going to set up a full data science environment for Mac users.\nIn the next vide...", |
|
"Video: 60619299<br>Text: Well, I hope you found that both educational and enjoyable.\nAs we went through and learned so much a...", |
|
"Video: 59295607<br>Text: So to revisit then the solution that we built in the previous day and talk about the metrics.\nAs I s...", |
|
"Video: 59297575<br>Text: Well, welcome to the final part on rag.\nAnd this is the session where you go from being a rag expert...", |
|
"Video: 59507687<br>Text: It's time for action, everybody.\nWe've set up our colab.\nHere we are, week seven, day three.\nWe've g...", |
|
"Video: 59671441<br>Text: And welcome once more to our favorite place to be Jupyter Lab, the Paradise for a data scientist exp...", |
|
"Video: 59673431<br>Text: And here we have it.\nThe user interface is completed.\nThe extra notification came through on my phon...", |
|
"Video: 59473137<br>Text: Let's get straight to it.\nSo the place where you can see everything that's going on and get knee dee...", |
|
"Video: 59166421<br>Text: Welcome back to the radio day in the lab.\nMore to do.\nLet's keep going.\nWhere we left off is we had ...", |
|
"Video: 59295599<br>Text: Welcome to the Jupyter Lab for day four.\nIt's going to look very familiar because it's actually I've...", |
|
"Video: 59669631<br>Text: Here we are in our favorite place to be in JupyterLab, ready for some coding and a lot of coding tha...", |
|
"Video: 59673663<br>Text: But wait, there's more.\nWe need to add some more to the user interface just to make it look more coo...", |
|
"Video: 59506929<br>Text: And we return to the hugging face open LLM leaderboard.\nThe first place you go when selecting your b...", |
|
"Video: 59504785<br>Text: So at this point we're going to talk about hyperparameters.\nAnd we're going to introduce three of th...", |
|
"Video: 59505337<br>Text: So we're now going to look at four bit quantization, the rather remarkable effect of reducing the pr...", |
|
"Video: 59271655<br>Text: So here we are on Hugging Face's main landing page at Hugging Face Core.\nA URL you know.\nWell, since...", |
|
"Video: 59472883<br>Text: Okay, time to reveal the results.\nIt has run to completion.\nAnd here it is.\nSo a moment to pause.\nIt...", |
|
"Video: 59673639<br>Text: And welcome now to the code for our user interface, which we will find in this Python module.\nPrice ...", |
|
"Video: 59472463<br>Text: So last time we looked at a humble linear regression model with feature engineering, and now we say\n...", |
|
"Video: 59297595<br>Text: So by the time you're watching this, hopefully you have played yourself with vectors.\nYou've created...", |
|
"Video: 60619149<br>Text: So we're going to start our exploration into the world of frontier models by playing with the famous...", |
|
"Video: 59297735<br>Text: And at last the time has come to see rag in action.\nAfter all of this talk, and here we are.\nWe're i...", |
|
"Video: 60616407<br>Text: And now over to my Mac people.\nAnd I have news for you.\nIt's exactly the same thing.\nYou go to a fav...", |
|
"Video: 59170235<br>Text: So here we are in Google Colab for our first collaborative session on the cloud using a GPU box.\nOn ...", |
|
"Video: 59472067<br>Text: So we've covered steps 1 to 4 of the five step strategy.\nAnd that brings us to step five, which is p...", |
|
"Video: 59472011<br>Text: Welcome everybody.\nSo in the past I've said quite a few times, I am excited to start this this week ...", |
|
"Video: 59295553<br>Text: Welcome back.\nIn the last part, we gave our GPT four and clawed the challenge of converting a simple...", |
|
"Video: 59297773<br>Text: Well, I hope you're eager with anticipation for this session in JupyterLab as we finally get to see\n...", |
|
"Video: 59295583<br>Text: And here we are back in JupyterLab.\nIt's been a minute.\nWe've been working in Colab for last week, a...", |
|
"Video: 59507329<br>Text: Okay.\nIt's moment of truth time.\nI have just taken our class tester.\nYou remember this class?\nUh, it...", |
|
"Video: 59295429<br>Text: Continuing our investigation of benchmarks, and this will become more real when we actually see some...", |
|
"Video: 60595637<br>Text: Here we are back in the Colab, which has been running overnight for me and probably for you too, I\nh...", |
|
"Video: 59668027<br>Text: And so here we are at the home page for modal.\nAt modal.com spelt model not not model which is confu...", |
|
"Video: 59295527<br>Text: I'm so happy to welcome you to week four, day four on our journey to LLM Engineering and Mastery.\nHe...", |
|
"Video: 59295377<br>Text: Just before we go on to some of the more advanced metrics, I want to mention for a second something\n...", |
|
"Video: 59666211<br>Text: So before we try our new model and one more recap on the models so far and keep notes of this so we\n...", |
|
"Video: 59170107<br>Text: And once again, it's that moment when you take a pause and congratulate yourself on another day of\ns...", |
|
"Video: 60616833<br>Text: So I realized that day one of week one has been a pretty long day, and I assure you that the other,\n...", |
|
"Video: 59472413<br>Text: Wonderful.\nWhere we left off is we had just created the Get Features function, which builds our feat...", |
|
"Video: 59297561<br>Text: And would you believe at this point you're 55% of the way along the journey?\nUh, it's been a while s...", |
|
"Video: 59669211<br>Text: Well, we took on a lot today and we seem to have been successful.\nThese red icons that you see on th...", |
|
"Video: 59166981<br>Text: Welcome to week two, day five.\nThe last day of week two where a lot is coming together.\nI am so grat...", |
|
"Video: 60619227<br>Text: And now let's move to Claude from anthropic, my favorite model and typically the favorite model of\nm...", |
|
"Video: 60620395<br>Text: Welcome back to Jupyter Lab, where I want to show you the assignment, the homework exercise for you\n...", |
|
"Video: 59665127<br>Text: Well hi there everybody.\nI'm not going to give you my usual song and dance about how excited you are...", |
|
"Video: 59668923<br>Text: Well, welcome back to Jupyter Lab for what will be an epic finale to our time in this platform.\nAnd ...", |
|
"Video: 59504887<br>Text: Well, here we are again in Google Colab.\nIt's been a minute since we were here, and welcome back to ...", |
|
"Video: 59170165<br>Text: Welcome, everybody to the last day of week three.\nWeek three.\nDay five.\nWe're here already wrapping ...", |
|
"Video: 60617251<br>Text: Congratulations are definitely in order.\nYesterday was a mammoth first day on this course and you go...", |
|
"Video: 59166951<br>Text: All right, back to the lab.\nBack to our project.\nTime to work with tools.\nI am in the week two folde...", |
|
"Video: 60619619<br>Text: Well, day four was an information dense day.\nI do hope that you learned some something useful here, ...", |
|
"Video: 60616663<br>Text: Well.\nHi there, this is time for PC people to get set up.\nSo all you Mac people out there, you don't...", |
|
"Video: 59508175<br>Text: So I'm taking a moment now to explain that the training costs of optimizing a model for this course\n...", |
|
"Video: 59670087<br>Text: And welcome to part four of day two of week eight.\nUh, there's a lot happening this week, and I have...", |
|
"Video: 59506713<br>Text: Hi everyone.\nSo the reason I'm so fired up about week seven is that this is the time when we actuall...", |
|
"Video: 60620169<br>Text: Hopefully you found this super satisfying to be able to have this nice business result and have it c...", |
|
"Video: 59295435<br>Text: Well, just before we wrap up, let me introduce this week's challenge and talk about what we're going...", |
|
"Video: 59297609<br>Text: Last week, we worked with models that were able to speed up code by a factor of 60,000 times, which\n...", |
|
"Video: 59507489<br>Text: Continuing our adventure through hyperparameters for training.\nThe next one is pretty crucial and it...", |
|
"Video: 59295549<br>Text: And welcome back to our challenge again.\nAnd this time we are working with our beautiful prototype.\n...", |
|
"Video: 59665129<br>Text: And now let me make this real for you by showing you some, some diagrams, particularly now looking\na...", |
|
"Video: 59169991<br>Text: Okay, so that was your introduction to Hugging Face.\nAnd now I'm going to turn to a different resour...", |
|
"Video: 59472027<br>Text: And now the time has come to curate our data set.\nAnd the way we're going to do this is we're going ...", |
|
"Video: 59472307<br>Text: Welcome to week six.\nDay two a day.\nWhen we get back into the data, we look back in anger at our dat...", |
|
"Video: 59508289<br>Text: So here we are now, back in the Colab, in the same one that we kicked off in the previous day.\nIt's ...", |
|
"Video: 59472333<br>Text: Thank you for putting up with me during my foray into traditional machine learning.\nI think it was u...", |
|
"Video: 59295431<br>Text: Now I want to take a quick moment to give you a flyby of five different ways that llms are used comm...", |
|
"Video: 59673449<br>Text: Well, I have to tell you that I'm a little bit sad.\nThis is the beginning of the beginning of the en...", |
|
"Video: 59669389<br>Text: Well.\nHi there.\nSo you've made it to day two of week eight, and I am super grateful that you've been...", |
|
"Video: 59170057<br>Text: And so at the beginning of this week, we started by talking about hugging face pipelines.\nAnd you us...", |
|
"Video: 59166949<br>Text: Welcome back to making chatbots.\nLet's keep going.\nSo for the next part we're going to beef up the s...", |
|
"Video: 59473019<br>Text: Welcome back to an action packed time of of training.\nSo now, after waiting about five minutes when ...", |
|
"Video: 59297585<br>Text: Before we move on, let me show you one more time this fabulous slide that describes the simple three...", |
|
"Video: 59170255<br>Text: And welcome back to us continuing our journey through the model class in Hugging Face Transformers l...", |
|
"Video: 60614589<br>Text: So we're now going to run a large language model directly on your box using a platform called llama,...", |
|
"Video: 59297601<br>Text: I'm not going to lie, at this point you have every reason to be impatient with me.\nWe've been yammer...", |
|
"Video: 60616629<br>Text: And welcome back to team PC and Team Mac as we come back together again for a quick video.\nIn this o...", |
|
"Video: 59297749<br>Text: It's always welcome back to JupyterLab, my favorite place to be.\nAnd now we are, of course in the we...", |
|
"Video: 59170135<br>Text: Welcome.\nIt's week three.\nIt's day four.\nWe are back on the adventure in open source land, back inve...", |
|
"Video: 59472017<br>Text: And this is the first time that we'll be coding against our big project of the course.\nWelcome to Ju...", |
|
"Video: 59507017<br>Text: Welcome to Colab.\nWelcome to the week seven day two Colab.\nAnd just before we try our base model, we...", |
|
"Video: 60619883<br>Text: And now we've arrived at an exciting moment in our first week.\nThe conclusion of the first week is w...", |
|
"Video: 59508297<br>Text: What more is there to say, really?\nTomorrow is the day for results.\nA day that very excited indeed a...", |
|
"Video: 60619247<br>Text: We're going to spend a little bit more time with GPT just to try out a few more interesting things.\n...", |
|
"Video: 59504769<br>Text: Without further ado, we're going to get stuck into it.\nTalking about Laura.\nLow rank adaptation.\nAnd...", |
|
"Video: 59170233<br>Text: Welcome back to our continued exploits with Tokenizers.\nWhat we're now going to look at is what's ca...", |
|
"Video: 59671231<br>Text: And here we are back in the Jupyter Lab for the fast approaching conclusion with a really great proj...", |
|
"Video: 60620397<br>Text: Well, that's a fantastic result to have now arrived towards the end of week one and having completed...", |
|
"Video: 59170093<br>Text: I'm delighted to see you again.\nAs we get started with day three of week three of our adventure and ...", |
|
"Video: 59473089<br>Text: Welcome back.\nSo hopefully you are still impressed by the GPT four mini results.\nThe frontier model ...", |
|
"Video: 60395261<br>Text: Let's keep going with our project to equip our LM with a tool.\nWe just created this piece of code to...", |
|
"Video: 60617259<br>Text: I'm excited to introduce you to your first exercise, and I'm looking forward to seeing what you make...", |
|
"Video: 59507313<br>Text: And it's this time again, when we look at the podium of how our models are performing across the boa...", |
|
"Video: 60619721<br>Text: Now it's time to talk for a minute about tokens.\nTokens are the individual units which get passed in...", |
|
"Video: 59295451<br>Text: I know that everybody.\nIt seems like just the other day that we were embarking on our quest together...", |
|
"Video: 59166919<br>Text: And with that, it concludes our session on tools.\nAnd at this point, you are probably an expert on t...", |
|
"Video: 59295441<br>Text: Okay, so welcome to our leaderboard fast as we go through a ton of essential leaderboards for your\nc...", |
|
"Video: 59295541<br>Text: And welcome back.\nYou've just seen GPT four zero spectacularly failed to work on our hard Python con...", |
|
"Video: 59473101<br>Text: Welcome back.\nSo about ten minutes later, maybe 15 minutes later, the run has completed.\nAnd how do ...", |
|
"Video: 59507423<br>Text: So you may remember eons ago when we were building our data set.\nAt the end of that, we uploaded our...", |
|
"Video: 59295545<br>Text: I really hope you've enjoyed this week.\nWe've got tons done.\nWe've experimented with all sorts of ne...", |
|
"Video: 59472503<br>Text: Welcome back to Jupyter Lab.\nLast time, we looked at some silly models for predicting the price of p...", |
|
"Video: 60614591<br>Text: The mantra of this course is that the best way to learn is by doing, and we will be doing stuff toge...", |
|
"Video: 59473021<br>Text: Welcome to our favorite place to be to JupyterLab.\nHere we are again now in day three.\nIn week six.\n...", |
|
"Video: 60617255<br>Text: I'm now going to talk for a bit about models.\nA term you often hear is the term frontier models, whi...", |
|
"Video: 59667829<br>Text: Well.\nHello there.\nLook, I know what you're thinking.\nYou're thinking I peaked too early.\nLast week ...", |
|
"Video: 59505329<br>Text: Welcome back.\nYou may, like me, have just gone off and got a coffee while things loaded back up agai...", |
|
"Video: 59669049<br>Text: So what you just saw was an ephemeral app, as it's called, which means just a temporary app that you...", |
|
"Video: 60619439<br>Text: This now brings us to an extremely important property of LMS called the context window that I want t...", |
|
"Video: 59668181<br>Text: And so it gives me great pleasure to introduce to you the project that I've lined up for you this we...", |
|
"Video: 59472441<br>Text: Welcome back.\nSo we've been doing the thoroughly distasteful, unsavory work of feature engineering.\n...", |
|
"Video: 59507785<br>Text: Well, I'm sure you're fed up of me saying that the moment of truth has arrived, but it really has.\nT...", |
|
"Video: 59295587<br>Text: When I left you, we had just created this simple user interface for converting from Python to C plus...", |
|
"Video: 59166465<br>Text: Welcome back to the JupyterLab on Gradio day, so you'll remember where we left off.\nWe'd written two...", |
|
"Video: 59473071<br>Text: Hey, gang.\nLook, I know what you're thinking.\nThis week was supposed to be training week.\nI set it a...", |
|
"Video: 59295423<br>Text: Welcome to day two of week four, when we get more into leaderboards so that by the end of this, you'...", |
|
"Video: 59297723<br>Text: So I know what you're thinking.\nYou're thinking, what's going on here?\nWe're on day five.\nWe're on d...", |
|
"Video: 59166947<br>Text: Well, thank you for coming along for week two, day four.\nWe have lots of good stuff in store today.\n...", |
|
"Video: 59666831<br>Text: Take one more moment to look at this very nice diagram that lays it all out, and we will move on.\nNo...", |
|
"Video: 59295493<br>Text: And welcome to week four, day three.\nAs we are about to embark upon another business project which w...", |
|
"Video: 60616855<br>Text: Now I know what you're thinking.\nWe've been building environments for so long.\nAre we not done yet?\n...", |
|
"Video: 59506611<br>Text: So in a future day, I'm going to be training, fine tuning a model and creating a fine tuned model.\nA...", |
|
"Video: 60616493<br>Text: I'll just take a quick moment to introduce myself to convince you that I am actually qualified to be...", |
|
"Video: 59166317<br>Text: And welcome to week two, day two, as we continue our adventure into the realm of LMS.\nUh, so today, ...", |
|
"Video: 59295439<br>Text: So I'm aware that there's a big risk that you are getting fed up of leaderboards, because we've done...", |
|
"Video: 59472421<br>Text: And welcome back to our final time in Jupyter Lab with traditional machine learning.\nIt's almost ove...", |
|
"Video: 59472137<br>Text: Well, well, well, it's been a long day, but congratulations, you've made it.\nWe've gone through and ...", |
|
"Video: 59297693<br>Text: So at the end of each week, it's customary for me to give you a challenge, an assignment to do on\nyo...", |
|
"Video: 60620143<br>Text: So we're going to make a call to GPT four.\nOh, that's going to ask it to look through a set of links...", |
|
"Video: 60619501<br>Text: I welcome to day four of our time together.\nThis is a very important day.\nToday we're going to be lo...", |
|
"Video: 59297743<br>Text: And welcome to day five.\nFor reals.\nWe're actually in the proper Jupyter notebook.\nThis time we're i...", |
|
"Video: 59166847<br>Text: Well, they say that time flies when you're having fun, and it certainly feels like time is flying.\nU...", |
|
"Video: 59170223<br>Text: Well.\nFantastic.\nIt's coming up to the end of the week, and that means it's coming up to a challenge...", |
|
"Video: 59170037<br>Text: So how does it feel to be 30% of the way down the journey to being a proficient LLM engineer?\nTake a...", |
|
"Video: 59295609<br>Text: You must be feeling absolutely exhausted at this point.\nAnd if you are, that is okay.\nYou have done ...", |
|
"Video: 60619281<br>Text: Well, I'm delighted to welcome you to day three of our eight week journey together.\nAnd today we're ...", |
|
"Video: 59472429<br>Text: And continuing on our strategy to solve commercial problems with LMS, we get to step four, which is\n...", |
|
"Video: 59167009<br>Text: Welcome back.\nIt's time to make our full agent framework.\nI'm super excited about this.\nIt's pulling...", |
|
"Video: 59166481<br>Text: And here, once more we find ourselves in our favorite place, the Jupyter Lab.\nReady to go with weeks...", |
|
"Video: 59670933<br>Text: I realized my enthusiasm for this project is a bit insane, but I have to tell you that I am very sat...", |
|
"Video: 59670073<br>Text: Okay, it's time to complete the Rag workflow in our Jupyter Lab on day 2.3.\nWe've got this function ...", |
|
"Video: 59673595<br>Text: That concludes a mammoth project.\nThree weeks in the making.\nIn the course of those three weeks, sta...", |
|
"Video: 59297603<br>Text: And I'm delighted to welcome you back to LM engineering on the day that we turn to vectors.\nFinally,...", |
|
"Video: 60614541<br>Text: I am delighted to welcome you to the first day of our eight weeks together as you join me on this ad...", |
|
"Video: 59667357<br>Text: Let's now see our results side by side.\nWe started our journey with a constant model that was at $1....", |
|
"Video: 59667841<br>Text: Now, look, I know that I went through that very fast, but maybe, uh, you're still, uh, blinking\nat t...", |
|
"Video: 59472007<br>Text: So I hope you enjoyed our first bash at Scrubbing Data, and that you are now looking through the cod...", |
|
"Video: 59507435<br>Text: So I'm now going to talk about five important hyperparameters for the training process.\nAnd some of ...", |
|
"Video: 59509185<br>Text: So this is where I left you looking at this satisfying chart on training loss and seeing the trainin...", |
|
"Video: 59473159<br>Text: Welcome to Jupyter Lab and welcome to our experiments at the frontier.\nSo we are going to put our fr...", |
|
"Video: 60619447<br>Text: I want to take a moment to talk about something that's very fundamental to an LLM, which is the numb...", |
|
"Video: 59166353<br>Text: Well, congratulations on leveling up yet again.\nYou've got some real hard skills that you've added t...", |
|
"Video: 60619123<br>Text: So what we're now going to do is we're going to look at some models in practice and start to compare...", |
|
"Video: 59295363<br>Text: Well, another congratulations moment.\nYou have 40% on the way to being an LM engineer at a high leve...", |
|
"Video: 60619289<br>Text: And now we'll go a bit faster through the other models.\nWe'll start with Google's Gemini.\nI have the...", |
|
"Video: 59472873<br>Text: So it's quite an adventure that we had at the frontier of what's capable with Llms today, solving a\n...", |
|
"Video: 60619429<br>Text: Let me talk about some other phenomena that have happened over the last few years.\nOne of them has b...", |
|
"Video: 59295601<br>Text: So it's time to continue our journey into the world of open source and understand which models we sh...", |
|
"Video: 59170025<br>Text: And a massive welcome back one more time to LM engineering.\nWe are in week three, day two and we are...", |
|
"Video: 59166443<br>Text: And welcome back everybody.\nWelcome to week two day three.\nIt's a continuation of our enjoyment of r...", |
|
"Video: 60620025<br>Text: And welcome back to Jupyter Lab, one of my very favorite places to be.\nWhen Jupyter Lab sprung up on...", |
|
"Video: 59170055<br>Text: Welcome to the world of Google Colab.\nYou may already be very familiar with Google Colab, even if so..." |
|
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"gridcolor": "white", |
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"linecolor": "white", |
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"ticks": "" |
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}, |
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"bgcolor": "#E5ECF6", |
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"caxis": { |
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"gridcolor": "white", |
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"linecolor": "white", |
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"ticks": "" |
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} |
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}, |
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"title": { |
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"x": 0.05 |
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}, |
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"xaxis": { |
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"automargin": true, |
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"gridcolor": "white", |
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"linecolor": "white", |
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"ticks": "", |
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"title": { |
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"standoff": 15 |
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}, |
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"zerolinecolor": "white", |
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"zerolinewidth": 2 |
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}, |
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"yaxis": { |
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"automargin": true, |
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"gridcolor": "white", |
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"linecolor": "white", |
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"ticks": "", |
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"title": { |
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"standoff": 15 |
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}, |
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"zerolinecolor": "white", |
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"zerolinewidth": 2 |
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} |
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} |
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}, |
|
"title": { |
|
"text": "2D Chroma Vector Store Visualization" |
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}, |
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"width": 800 |
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} |
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}, |
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"image/png": 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interface.\\nBut fi...\",\"Video: 60617163\\u003cbr\\u003eText: And already that wraps up day two.\\nNow that you have built that solution.\\nAnd congratulations on tha...\",\"Video: 60616423\\u003cbr\\u003eText: So I hope you've just enjoyed yourself experimenting with different LMS locally on your box using th...\",\"Video: 59170227\\u003cbr\\u003eText: Welcome back to Google Colab.\\nHere we are ready to explore the wonderful world of Tokenizers.\\nSo, uh...\",\"Video: 59169985\\u003cbr\\u003eText: So I hope you enjoyed that whirlwind tour of Google Colab.\\nHere's just a little screenshot example o...\",\"Video: 60616927\\u003cbr\\u003eText: It's time for our first LM experiment at this point.\\nSo some of this you may know well, you may know...\",\"Video: 59673721\\u003cbr\\u003eText: And here we are in JupyterLab for the last time, and we are looking here at day five, the last day\\no...\",\"Video: 59508055\\u003cbr\\u003eText: I'm so very happy that you've reached this epic moment in the course and that you're hanging in ther...\",\"Video: 59670259\\u003cbr\\u003eText: It's remarkable.\\nBut you are now at the 95% point.\\nThere's 5% remaining of this course.\\nUh, maybe it...\",\"Video: 60616623\\u003cbr\\u003eText: So we're now going to start week one of the course when we are going to be looking at exploring fron...\",\"Video: 59472383\\u003cbr\\u003eText: And welcome back to the week six folder.\\nWe're now at day two, which is the second and final stage o...\",\"Video: 59670171\\u003cbr\\u003eText: So as the very final step on this part four of day two of week eight, we are now going to build an\\ne...\",\"Video: 59297721\\u003cbr\\u003eText: And so now the time has come to talk about the most crucial aspect of Rag, which is the idea of vect...\",\"Video: 59297599\\u003cbr\\u003eText: Well, that was a sneaky detour I took you on in the last one.\\nI hope you enjoyed it though, and I ho...\",\"Video: 59507635\\u003cbr\\u003eText: Look, I hope you're excited.\\nYou really should be.\\nYou've been through 80% of the course and it's al...\",\"Video: 59669375\\u003cbr\\u003eText: Here we are for the day.\\n2.1 notebook.\\nAnd don't let it be said that I don't ever do anything for yo...\",\"Video: 59297733\\u003cbr\\u003eText: Welcome back to JupyterLab and welcome to your first experiment with the world of Long Chain.\\nLet me...\",\"Video: 59670369\\u003cbr\\u003eText: It is terrific that you're hanging on in there and making such great progress with this course.\\nAs w...\",\"Video: 59166281\\u003cbr\\u003eText: And with that, amazingly, you completed day one of week two already and that gets you to the 15% poi...\",\"Video: 59671567\\u003cbr\\u003eText: Well, the first thing you're going to notice is that I don't have a notebook open for you.\\nAnd that'...\",\"Video: 59297593\\u003cbr\\u003eText: And welcome to continuing our journey with Hrag.\\nAnd today it's time to unveil Liang Chen.\\nSo first,...\",\"Video: 59166461\\u003cbr\\u003eText: And welcome back to the lab.\\nHere we are in Jupyter Lab and we are going to go into week two.\\nAnd we...\",\"Video: 59167007\\u003cbr\\u003eText: Well, how fabulous is that?\\nI hope that you are as wowed as I am by our new airline, I assistant and...\",\"Video: 59508121\\u003cbr\\u003eText: The moment has arrived.\\nHere we go.\\nWe're in fine tuning.\\nWe do fine tuning.\\nTrain.\\nThere is also a ...\",\"Video: 59295579\\u003cbr\\u003eText: All right.\\nAre you excited to see how this goes?\\nLet's give it a try.\\nSo in this next section, I cre...\",\"Video: 60620375\\u003cbr\\u003eText: And with that, we've reached an important milestone.\\nThe first week of our eight week journey is com...\",\"Video: 59472491\\u003cbr\\u003eText: Welcome back.\\nIf you are following along with me in JupyterLab, as I hope you are, then you will nee...\",\"Video: 59472425\\u003cbr\\u003eText: Welcome to week six, day three.\\nToday is going to be a day that you will either love or you will hat...\",\"Video: 59508057\\u003cbr\\u003eText: Actually slight change in plan.\\nI'm going to wrap up the day.\\nDay three at this point, and say that ...\",\"Video: 60619577\\u003cbr\\u003eText: And for the final piece of background information, I wanted to take another moment to talk about API...\",\"Video: 59170291\\u003cbr\\u003eText: Welcome back to Colab and welcome back to our business project.\\nSo again our assignment, we are due ...\",\"Video: 60619651\\u003cbr\\u003eText: I mentioned before an AI company called vellum.\\nWhen we were talking about the different questions, ...\",\"Video: 59473191\\u003cbr\\u003eText: And you thought we'd never get here.\\nHere we are in Jupyter Lab, running our fine tuning for a front...\",\"Video: 59170297\\u003cbr\\u003eText: And here we are in Google Colab, ready for fun with models.\\nSo first we do the usual Pip installs an...\",\"Video: 59167015\\u003cbr\\u003eText: Welcome back to Jupyter Lab and welcome to Day Five's Lab.\\nAnd this is going to be lots of creativit...\",\"Video: 59170043\\u003cbr\\u003eText: Let me enthusiastically welcome you all back to week three of our LLM engineering journey.\\nIf you en...\",\"Video: 59473147\\u003cbr\\u003eText: Well, I'm very relieved.\\nI've got that behind me.\\nNo more human testing for me.\\nWe'll have one final...\",\"Video: 59166453\\u003cbr\\u003eText: Welcome back and welcome to our continuing JupyterLab experience.\\nUh, I'm hopefully going to keep yo...\",\"Video: 59166915\\u003cbr\\u003eText: Welcome back to the wonderful world of JupyterLab.\\nAnd here we are in week two.\\nDay three.\\nUh, bring...\",\"Video: 59667365\\u003cbr\\u003eText: Here we are back in Colab, looking at the week seven, day five of the Colab notebooks and I'm on a\\nT...\",\"Video: 60616845\\u003cbr\\u003eText: We're on the home stretch.\\nThis is the final step in the environment setup, and it's an easy one.\\nIt...\",\"Video: 59295459\\u003cbr\\u003eText: And welcome back to More Leaderboard Fest as we go through some more leaderboards.\\nBut this time we'...\",\"Video: 59471979\\u003cbr\\u003eText: So we now turn to the parts of the problem, which is perhaps, let's say, not as glamorous as some\\nof...\",\"Video: 59503705\\u003cbr\\u003eText: And so now we talk about quantization the q and q Laura.\\nQ stands for quantized quantized.\\nLaura.\\nAn...\",\"Video: 59472505\\u003cbr\\u003eText: So the good news is that this is the very final video about data set curation.\\nYou were probably fed...\",\"Video: 59669217\\u003cbr\\u003eText: And welcome to the next part of visualizing the data.\\nAnd just very quickly to show it to you in 3D....\",\"Video: 59671221\\u003cbr\\u003eText: I gotta tell you, I don't like to toot my horn a whole lot, but I do think that I've done a great\\njo...\",\"Video: 59503703\\u003cbr\\u003eText: Well.\\nHello there everybody.\\nI am so grateful that you've made it through to the start of week seven...\",\"Video: 59473201\\u003cbr\\u003eText: Well, before we do a postmortem on what happened, let's just quickly look at the standing the rankin...\",\"Video: 60622463\\u003cbr\\u003eText: In this video, we're going to set up a full data science environment for Mac users.\\nIn the next vide...\",\"Video: 60619299\\u003cbr\\u003eText: Well, I hope you found that both educational and enjoyable.\\nAs we went through and learned so much a...\",\"Video: 59295607\\u003cbr\\u003eText: So to revisit then the solution that we built in the previous day and talk about the metrics.\\nAs I s...\",\"Video: 59297575\\u003cbr\\u003eText: Well, welcome to the final part on rag.\\nAnd this is the session where you go from being a rag expert...\",\"Video: 59507687\\u003cbr\\u003eText: It's time for action, everybody.\\nWe've set up our colab.\\nHere we are, week seven, day three.\\nWe've g...\",\"Video: 59671441\\u003cbr\\u003eText: And welcome once more to our favorite place to be Jupyter Lab, the Paradise for a data scientist exp...\",\"Video: 59673431\\u003cbr\\u003eText: And here we have it.\\nThe user interface is completed.\\nThe extra notification came through on my phon...\",\"Video: 59473137\\u003cbr\\u003eText: Let's get straight to it.\\nSo the place where you can see everything that's going on and get knee dee...\",\"Video: 59166421\\u003cbr\\u003eText: Welcome back to the radio day in the lab.\\nMore to do.\\nLet's keep going.\\nWhere we left off is we had ...\",\"Video: 59295599\\u003cbr\\u003eText: Welcome to the Jupyter Lab for day four.\\nIt's going to look very familiar because it's actually I've...\",\"Video: 59669631\\u003cbr\\u003eText: Here we are in our favorite place to be in JupyterLab, ready for some coding and a lot of coding tha...\",\"Video: 59673663\\u003cbr\\u003eText: But wait, there's more.\\nWe need to add some more to the user interface just to make it look more coo...\",\"Video: 59506929\\u003cbr\\u003eText: And we return to the hugging face open LLM leaderboard.\\nThe first place you go when selecting your b...\",\"Video: 59504785\\u003cbr\\u003eText: So at this point we're going to talk about hyperparameters.\\nAnd we're going to introduce three of th...\",\"Video: 59505337\\u003cbr\\u003eText: So we're now going to look at four bit quantization, the rather remarkable effect of reducing the pr...\",\"Video: 59271655\\u003cbr\\u003eText: So here we are on Hugging Face's main landing page at Hugging Face Core.\\nA URL you know.\\nWell, since...\",\"Video: 59472883\\u003cbr\\u003eText: Okay, time to reveal the results.\\nIt has run to completion.\\nAnd here it is.\\nSo a moment to pause.\\nIt...\",\"Video: 59673639\\u003cbr\\u003eText: And welcome now to the code for our user interface, which we will find in this Python module.\\nPrice ...\",\"Video: 59472463\\u003cbr\\u003eText: So last time we looked at a humble linear regression model with feature engineering, and now we say\\n...\",\"Video: 59297595\\u003cbr\\u003eText: So by the time you're watching this, hopefully you have played yourself with vectors.\\nYou've created...\",\"Video: 60619149\\u003cbr\\u003eText: So we're going to start our exploration into the world of frontier models by playing with the famous...\",\"Video: 59297735\\u003cbr\\u003eText: And at last the time has come to see rag in action.\\nAfter all of this talk, and here we are.\\nWe're i...\",\"Video: 60616407\\u003cbr\\u003eText: And now over to my Mac people.\\nAnd I have news for you.\\nIt's exactly the same thing.\\nYou go to a fav...\",\"Video: 59170235\\u003cbr\\u003eText: So here we are in Google Colab for our first collaborative session on the cloud using a GPU box.\\nOn ...\",\"Video: 59472067\\u003cbr\\u003eText: So we've covered steps 1 to 4 of the five step strategy.\\nAnd that brings us to step five, which is p...\",\"Video: 59472011\\u003cbr\\u003eText: Welcome everybody.\\nSo in the past I've said quite a few times, I am excited to start this this week ...\",\"Video: 59295553\\u003cbr\\u003eText: Welcome back.\\nIn the last part, we gave our GPT four and clawed the challenge of converting a simple...\",\"Video: 59297773\\u003cbr\\u003eText: Well, I hope you're eager with anticipation for this session in JupyterLab as we finally get to see\\n...\",\"Video: 59295583\\u003cbr\\u003eText: And here we are back in JupyterLab.\\nIt's been a minute.\\nWe've been working in Colab for last week, a...\",\"Video: 59507329\\u003cbr\\u003eText: Okay.\\nIt's moment of truth time.\\nI have just taken our class tester.\\nYou remember this class?\\nUh, it...\",\"Video: 59295429\\u003cbr\\u003eText: Continuing our investigation of benchmarks, and this will become more real when we actually see some...\",\"Video: 60595637\\u003cbr\\u003eText: Here we are back in the Colab, which has been running overnight for me and probably for you too, I\\nh...\",\"Video: 59668027\\u003cbr\\u003eText: And so here we are at the home page for modal.\\nAt modal.com spelt model not not model which is confu...\",\"Video: 59295527\\u003cbr\\u003eText: I'm so happy to welcome you to week four, day four on our journey to LLM Engineering and Mastery.\\nHe...\",\"Video: 59295377\\u003cbr\\u003eText: Just before we go on to some of the more advanced metrics, I want to mention for a second something\\n...\",\"Video: 59666211\\u003cbr\\u003eText: So before we try our new model and one more recap on the models so far and keep notes of this so we\\n...\",\"Video: 59170107\\u003cbr\\u003eText: And once again, it's that moment when you take a pause and congratulate yourself on another day of\\ns...\",\"Video: 60616833\\u003cbr\\u003eText: So I realized that day one of week one has been a pretty long day, and I assure you that the other,\\n...\",\"Video: 59472413\\u003cbr\\u003eText: Wonderful.\\nWhere we left off is we had just created the Get Features function, which builds our feat...\",\"Video: 59297561\\u003cbr\\u003eText: And would you believe at this point you're 55% of the way along the journey?\\nUh, it's been a while s...\",\"Video: 59669211\\u003cbr\\u003eText: Well, we took on a lot today and we seem to have been successful.\\nThese red icons that you see on th...\",\"Video: 59166981\\u003cbr\\u003eText: Welcome to week two, day five.\\nThe last day of week two where a lot is coming together.\\nI am so grat...\",\"Video: 60619227\\u003cbr\\u003eText: And now let's move to Claude from anthropic, my favorite model and typically the favorite model of\\nm...\",\"Video: 60620395\\u003cbr\\u003eText: Welcome back to Jupyter Lab, where I want to show you the assignment, the homework exercise for you\\n...\",\"Video: 59665127\\u003cbr\\u003eText: Well hi there everybody.\\nI'm not going to give you my usual song and dance about how excited you are...\",\"Video: 59668923\\u003cbr\\u003eText: Well, welcome back to Jupyter Lab for what will be an epic finale to our time in this platform.\\nAnd ...\",\"Video: 59504887\\u003cbr\\u003eText: Well, here we are again in Google Colab.\\nIt's been a minute since we were here, and welcome back to ...\",\"Video: 59170165\\u003cbr\\u003eText: Welcome, everybody to the last day of week three.\\nWeek three.\\nDay five.\\nWe're here already wrapping ...\",\"Video: 60617251\\u003cbr\\u003eText: Congratulations are definitely in order.\\nYesterday was a mammoth first day on this course and you go...\",\"Video: 59166951\\u003cbr\\u003eText: All right, back to the lab.\\nBack to our project.\\nTime to work with tools.\\nI am in the week two folde...\",\"Video: 60619619\\u003cbr\\u003eText: Well, day four was an information dense day.\\nI do hope that you learned some something useful here, ...\",\"Video: 60616663\\u003cbr\\u003eText: Well.\\nHi there, this is time for PC people to get set up.\\nSo all you Mac people out there, you don't...\",\"Video: 59508175\\u003cbr\\u003eText: So I'm taking a moment now to explain that the training costs of optimizing a model for this course\\n...\",\"Video: 59670087\\u003cbr\\u003eText: And welcome to part four of day two of week eight.\\nUh, there's a lot happening this week, and I have...\",\"Video: 59506713\\u003cbr\\u003eText: Hi everyone.\\nSo the reason I'm so fired up about week seven is that this is the time when we actuall...\",\"Video: 60620169\\u003cbr\\u003eText: Hopefully you found this super satisfying to be able to have this nice business result and have it c...\",\"Video: 59295435\\u003cbr\\u003eText: Well, just before we wrap up, let me introduce this week's challenge and talk about what we're going...\",\"Video: 59297609\\u003cbr\\u003eText: Last week, we worked with models that were able to speed up code by a factor of 60,000 times, which\\n...\",\"Video: 59507489\\u003cbr\\u003eText: Continuing our adventure through hyperparameters for training.\\nThe next one is pretty crucial and it...\",\"Video: 59295549\\u003cbr\\u003eText: And welcome back to our challenge again.\\nAnd this time we are working with our beautiful prototype.\\n...\",\"Video: 59665129\\u003cbr\\u003eText: And now let me make this real for you by showing you some, some diagrams, particularly now looking\\na...\",\"Video: 59169991\\u003cbr\\u003eText: Okay, so that was your introduction to Hugging Face.\\nAnd now I'm going to turn to a different resour...\",\"Video: 59472027\\u003cbr\\u003eText: And now the time has come to curate our data set.\\nAnd the way we're going to do this is we're going ...\",\"Video: 59472307\\u003cbr\\u003eText: Welcome to week six.\\nDay two a day.\\nWhen we get back into the data, we look back in anger at our dat...\",\"Video: 59508289\\u003cbr\\u003eText: So here we are now, back in the Colab, in the same one that we kicked off in the previous day.\\nIt's ...\",\"Video: 59472333\\u003cbr\\u003eText: Thank you for putting up with me during my foray into traditional machine learning.\\nI think it was u...\",\"Video: 59295431\\u003cbr\\u003eText: Now I want to take a quick moment to give you a flyby of five different ways that llms are used comm...\",\"Video: 59673449\\u003cbr\\u003eText: Well, I have to tell you that I'm a little bit sad.\\nThis is the beginning of the beginning of the en...\",\"Video: 59669389\\u003cbr\\u003eText: Well.\\nHi there.\\nSo you've made it to day two of week eight, and I am super grateful that you've been...\",\"Video: 59170057\\u003cbr\\u003eText: And so at the beginning of this week, we started by talking about hugging face pipelines.\\nAnd you us...\",\"Video: 59166949\\u003cbr\\u003eText: Welcome back to making chatbots.\\nLet's keep going.\\nSo for the next part we're going to beef up the s...\",\"Video: 59473019\\u003cbr\\u003eText: Welcome back to an action packed time of of training.\\nSo now, after waiting about five minutes when ...\",\"Video: 59297585\\u003cbr\\u003eText: Before we move on, let me show you one more time this fabulous slide that describes the simple three...\",\"Video: 59170255\\u003cbr\\u003eText: And welcome back to us continuing our journey through the model class in Hugging Face Transformers l...\",\"Video: 60614589\\u003cbr\\u003eText: So we're now going to run a large language model directly on your box using a platform called llama,...\",\"Video: 59297601\\u003cbr\\u003eText: I'm not going to lie, at this point you have every reason to be impatient with me.\\nWe've been yammer...\",\"Video: 60616629\\u003cbr\\u003eText: And welcome back to team PC and Team Mac as we come back together again for a quick video.\\nIn this o...\",\"Video: 59297749\\u003cbr\\u003eText: It's always welcome back to JupyterLab, my favorite place to be.\\nAnd now we are, of course in the we...\",\"Video: 59170135\\u003cbr\\u003eText: Welcome.\\nIt's week three.\\nIt's day four.\\nWe are back on the adventure in open source land, back inve...\",\"Video: 59472017\\u003cbr\\u003eText: And this is the first time that we'll be coding against our big project of the course.\\nWelcome to Ju...\",\"Video: 59507017\\u003cbr\\u003eText: Welcome to Colab.\\nWelcome to the week seven day two Colab.\\nAnd just before we try our base model, we...\",\"Video: 60619883\\u003cbr\\u003eText: And now we've arrived at an exciting moment in our first week.\\nThe conclusion of the first week is w...\",\"Video: 59508297\\u003cbr\\u003eText: What more is there to say, really?\\nTomorrow is the day for results.\\nA day that very excited indeed a...\",\"Video: 60619247\\u003cbr\\u003eText: We're going to spend a little bit more time with GPT just to try out a few more interesting things.\\n...\",\"Video: 59504769\\u003cbr\\u003eText: Without further ado, we're going to get stuck into it.\\nTalking about Laura.\\nLow rank adaptation.\\nAnd...\",\"Video: 59170233\\u003cbr\\u003eText: Welcome back to our continued exploits with Tokenizers.\\nWhat we're now going to look at is what's ca...\",\"Video: 59671231\\u003cbr\\u003eText: And here we are back in the Jupyter Lab for the fast approaching conclusion with a really great proj...\",\"Video: 60620397\\u003cbr\\u003eText: Well, that's a fantastic result to have now arrived towards the end of week one and having completed...\",\"Video: 59170093\\u003cbr\\u003eText: I'm delighted to see you again.\\nAs we get started with day three of week three of our adventure and ...\",\"Video: 59473089\\u003cbr\\u003eText: Welcome back.\\nSo hopefully you are still impressed by the GPT four mini results.\\nThe frontier model ...\",\"Video: 60395261\\u003cbr\\u003eText: Let's keep going with our project to equip our LM with a tool.\\nWe just created this piece of code to...\",\"Video: 60617259\\u003cbr\\u003eText: I'm excited to introduce you to your first exercise, and I'm looking forward to seeing what you make...\",\"Video: 59507313\\u003cbr\\u003eText: And it's this time again, when we look at the podium of how our models are performing across the boa...\",\"Video: 60619721\\u003cbr\\u003eText: Now it's time to talk for a minute about tokens.\\nTokens are the individual units which get passed in...\",\"Video: 59295451\\u003cbr\\u003eText: I know that everybody.\\nIt seems like just the other day that we were embarking on our quest together...\",\"Video: 59166919\\u003cbr\\u003eText: And with that, it concludes our session on tools.\\nAnd at this point, you are probably an expert on t...\",\"Video: 59295441\\u003cbr\\u003eText: Okay, so welcome to our leaderboard fast as we go through a ton of essential leaderboards for your\\nc...\",\"Video: 59295541\\u003cbr\\u003eText: And welcome back.\\nYou've just seen GPT four zero spectacularly failed to work on our hard Python con...\",\"Video: 59473101\\u003cbr\\u003eText: Welcome back.\\nSo about ten minutes later, maybe 15 minutes later, the run has completed.\\nAnd how do ...\",\"Video: 59507423\\u003cbr\\u003eText: So you may remember eons ago when we were building our data set.\\nAt the end of that, we uploaded our...\",\"Video: 59295545\\u003cbr\\u003eText: I really hope you've enjoyed this week.\\nWe've got tons done.\\nWe've experimented with all sorts of ne...\",\"Video: 59472503\\u003cbr\\u003eText: Welcome back to Jupyter Lab.\\nLast time, we looked at some silly models for predicting the price of p...\",\"Video: 60614591\\u003cbr\\u003eText: The mantra of this course is that the best way to learn is by doing, and we will be doing stuff toge...\",\"Video: 59473021\\u003cbr\\u003eText: Welcome to our favorite place to be to JupyterLab.\\nHere we are again now in day three.\\nIn week six.\\n...\",\"Video: 60617255\\u003cbr\\u003eText: I'm now going to talk for a bit about models.\\nA term you often hear is the term frontier models, whi...\",\"Video: 59667829\\u003cbr\\u003eText: Well.\\nHello there.\\nLook, I know what you're thinking.\\nYou're thinking I peaked too early.\\nLast week ...\",\"Video: 59505329\\u003cbr\\u003eText: Welcome back.\\nYou may, like me, have just gone off and got a coffee while things loaded back up agai...\",\"Video: 59669049\\u003cbr\\u003eText: So what you just saw was an ephemeral app, as it's called, which means just a temporary app that you...\",\"Video: 60619439\\u003cbr\\u003eText: This now brings us to an extremely important property of LMS called the context window that I want t...\",\"Video: 59668181\\u003cbr\\u003eText: And so it gives me great pleasure to introduce to you the project that I've lined up for you this we...\",\"Video: 59472441\\u003cbr\\u003eText: Welcome back.\\nSo we've been doing the thoroughly distasteful, unsavory work of feature engineering.\\n...\",\"Video: 59507785\\u003cbr\\u003eText: Well, I'm sure you're fed up of me saying that the moment of truth has arrived, but it really has.\\nT...\",\"Video: 59295587\\u003cbr\\u003eText: When I left you, we had just created this simple user interface for converting from Python to C plus...\",\"Video: 59166465\\u003cbr\\u003eText: Welcome back to the JupyterLab on Gradio day, so you'll remember where we left off.\\nWe'd written two...\",\"Video: 59473071\\u003cbr\\u003eText: Hey, gang.\\nLook, I know what you're thinking.\\nThis week was supposed to be training week.\\nI set it a...\",\"Video: 59295423\\u003cbr\\u003eText: Welcome to day two of week four, when we get more into leaderboards so that by the end of this, you'...\",\"Video: 59297723\\u003cbr\\u003eText: So I know what you're thinking.\\nYou're thinking, what's going on here?\\nWe're on day five.\\nWe're on d...\",\"Video: 59166947\\u003cbr\\u003eText: Well, thank you for coming along for week two, day four.\\nWe have lots of good stuff in store today.\\n...\",\"Video: 59666831\\u003cbr\\u003eText: Take one more moment to look at this very nice diagram that lays it all out, and we will move on.\\nNo...\",\"Video: 59295493\\u003cbr\\u003eText: And welcome to week four, day three.\\nAs we are about to embark upon another business project which w...\",\"Video: 60616855\\u003cbr\\u003eText: Now I know what you're thinking.\\nWe've been building environments for so long.\\nAre we not done yet?\\n...\",\"Video: 59506611\\u003cbr\\u003eText: So in a future day, I'm going to be training, fine tuning a model and creating a fine tuned model.\\nA...\",\"Video: 60616493\\u003cbr\\u003eText: I'll just take a quick moment to introduce myself to convince you that I am actually qualified to be...\",\"Video: 59166317\\u003cbr\\u003eText: And welcome to week two, day two, as we continue our adventure into the realm of LMS.\\nUh, so today, ...\",\"Video: 59295439\\u003cbr\\u003eText: So I'm aware that there's a big risk that you are getting fed up of leaderboards, because we've done...\",\"Video: 59472421\\u003cbr\\u003eText: And welcome back to our final time in Jupyter Lab with traditional machine learning.\\nIt's almost ove...\",\"Video: 59472137\\u003cbr\\u003eText: Well, well, well, it's been a long day, but congratulations, you've made it.\\nWe've gone through and ...\",\"Video: 59297693\\u003cbr\\u003eText: So at the end of each week, it's customary for me to give you a challenge, an assignment to do on\\nyo...\",\"Video: 60620143\\u003cbr\\u003eText: So we're going to make a call to GPT four.\\nOh, that's going to ask it to look through a set of links...\",\"Video: 60619501\\u003cbr\\u003eText: I welcome to day four of our time together.\\nThis is a very important day.\\nToday we're going to be lo...\",\"Video: 59297743\\u003cbr\\u003eText: And welcome to day five.\\nFor reals.\\nWe're actually in the proper Jupyter notebook.\\nThis time we're i...\",\"Video: 59166847\\u003cbr\\u003eText: Well, they say that time flies when you're having fun, and it certainly feels like time is flying.\\nU...\",\"Video: 59170223\\u003cbr\\u003eText: Well.\\nFantastic.\\nIt's coming up to the end of the week, and that means it's coming up to a challenge...\",\"Video: 59170037\\u003cbr\\u003eText: So how does it feel to be 30% of the way down the journey to being a proficient LLM engineer?\\nTake a...\",\"Video: 59295609\\u003cbr\\u003eText: You must be feeling absolutely exhausted at this point.\\nAnd if you are, that is okay.\\nYou have done ...\",\"Video: 60619281\\u003cbr\\u003eText: Well, I'm delighted to welcome you to day three of our eight week journey together.\\nAnd today we're ...\",\"Video: 59472429\\u003cbr\\u003eText: And continuing on our strategy to solve commercial problems with LMS, we get to step four, which is\\n...\",\"Video: 59167009\\u003cbr\\u003eText: Welcome back.\\nIt's time to make our full agent framework.\\nI'm super excited about this.\\nIt's pulling...\",\"Video: 59166481\\u003cbr\\u003eText: And here, once more we find ourselves in our favorite place, the Jupyter Lab.\\nReady to go with weeks...\",\"Video: 59670933\\u003cbr\\u003eText: I realized my enthusiasm for this project is a bit insane, but I have to tell you that I am very sat...\",\"Video: 59670073\\u003cbr\\u003eText: Okay, it's time to complete the Rag workflow in our Jupyter Lab on day 2.3.\\nWe've got this function ...\",\"Video: 59673595\\u003cbr\\u003eText: That concludes a mammoth project.\\nThree weeks in the making.\\nIn the course of those three weeks, sta...\",\"Video: 59297603\\u003cbr\\u003eText: And I'm delighted to welcome you back to LM engineering on the day that we turn to vectors.\\nFinally,...\",\"Video: 60614541\\u003cbr\\u003eText: I am delighted to welcome you to the first day of our eight weeks together as you join me on this ad...\",\"Video: 59667357\\u003cbr\\u003eText: Let's now see our results side by side.\\nWe started our journey with a constant model that was at $1....\",\"Video: 59667841\\u003cbr\\u003eText: Now, look, I know that I went through that very fast, but maybe, uh, you're still, uh, blinking\\nat t...\",\"Video: 59472007\\u003cbr\\u003eText: So I hope you enjoyed our first bash at Scrubbing Data, and that you are now looking through the cod...\",\"Video: 59507435\\u003cbr\\u003eText: So I'm now going to talk about five important hyperparameters for the training process.\\nAnd some of ...\",\"Video: 59509185\\u003cbr\\u003eText: So this is where I left you looking at this satisfying chart on training loss and seeing the trainin...\",\"Video: 59473159\\u003cbr\\u003eText: Welcome to Jupyter Lab and welcome to our experiments at the frontier.\\nSo we are going to put our fr...\",\"Video: 60619447\\u003cbr\\u003eText: I want to take a moment to talk about something that's very fundamental to an LLM, which is the numb...\",\"Video: 59166353\\u003cbr\\u003eText: Well, congratulations on leveling up yet again.\\nYou've got some real hard skills that you've added t...\",\"Video: 60619123\\u003cbr\\u003eText: So what we're now going to do is we're going to look at some models in practice and start to compare...\",\"Video: 59295363\\u003cbr\\u003eText: Well, another congratulations moment.\\nYou have 40% on the way to being an LM engineer at a high leve...\",\"Video: 60619289\\u003cbr\\u003eText: And now we'll go a bit faster through the other models.\\nWe'll start with Google's Gemini.\\nI have the...\",\"Video: 59472873\\u003cbr\\u003eText: So it's quite an adventure that we had at the frontier of what's capable with Llms today, solving a\\n...\",\"Video: 60619429\\u003cbr\\u003eText: Let me talk about some other phenomena that have happened over the last few years.\\nOne of them has b...\",\"Video: 59295601\\u003cbr\\u003eText: So it's time to continue our journey into the world of open source and understand which models we sh...\",\"Video: 59170025\\u003cbr\\u003eText: And a massive welcome back one more time to LM engineering.\\nWe are in week three, day two and we are...\",\"Video: 59166443\\u003cbr\\u003eText: And welcome back everybody.\\nWelcome to week two day three.\\nIt's a continuation of our enjoyment of r...\",\"Video: 60620025\\u003cbr\\u003eText: And welcome back to Jupyter Lab, one of my very favorite places to be.\\nWhen Jupyter Lab sprung up on...\",\"Video: 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"# We humans find it easier to visalize things in 2D!\n", |
|
"# Reduce the dimensionality of the vectors to 2D using t-SNE\n", |
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"# (t-distributed stochastic neighbor embedding)\n", |
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"\n", |
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"tsne = TSNE(n_components=2, random_state=42)\n", |
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"# Create the 2D scatter plot\n", |
|
"fig = go.Figure(data=[go.Scatter(\n", |
|
" x=reduced_vectors[:, 0],\n", |
|
" y=reduced_vectors[:, 1],\n", |
|
" mode='markers',\n", |
|
" marker=dict(size=5, color=colors, opacity=0.8),\n", |
|
" text=[f\"Video: {t}<br>Text: {d[:100]}...\" for t, d in zip(video_numbers , documents)],\n", |
|
" hoverinfo='text'\n", |
|
")])\n", |
|
"\n", |
|
"fig.update_layout(\n", |
|
" title='2D Chroma Vector Store Visualization',\n", |
|
" scene=dict(xaxis_title='x',yaxis_title='y'),\n", |
|
" width=800,\n", |
|
" height=600,\n", |
|
" margin=dict(r=20, b=10, l=10, t=40)\n", |
|
")\n", |
|
"\n", |
|
"fig.show()" |
|
] |
|
}, |
|
{ |
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"execution_count": 56, |
|
"id": "e1418e88-acd5-460a-bf2b-4e6efc88e3dd", |
|
"metadata": {}, |
|
"outputs": [ |
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{ |
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"data": { |
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"application/vnd.plotly.v1+json": { |
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"config": { |
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"plotlyServerURL": "https://plot.ly" |
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"text": [ |
|
"Video: 59506507<br>Text: Well, I realized that was a whole lot of theory, but I hope it gave you a good intuition that will\nb...", |
|
"Video: 59671315<br>Text: Okay, so here we are, back in Jupyter Lab, ready for the next use of a frontier model, and see this\n...", |
|
"Video: 60616895<br>Text: It feels like 100 videos ago that I told you that we were going to have instant gratification with o...", |
|
"Video: 60619275<br>Text: And we will conclude our expedition into the world of frontier models through their chat interface b...", |
|
"Video: 59472693<br>Text: Friends.\nI am absolutely exhausted.\nI am exhausted and a little tiny bit traumatized.\nAnd you are so...", |
|
"Video: 59670121<br>Text: So it's business time right now.\nWe are going to build a Rag pipeline to estimate the price of produ...", |
|
"Video: 59295619<br>Text: Welcome back to the the moment when we bring it all together into a beautiful user interface.\nBut fi...", |
|
"Video: 60617163<br>Text: And already that wraps up day two.\nNow that you have built that solution.\nAnd congratulations on tha...", |
|
"Video: 60616423<br>Text: So I hope you've just enjoyed yourself experimenting with different LMS locally on your box using th...", |
|
"Video: 59170227<br>Text: Welcome back to Google Colab.\nHere we are ready to explore the wonderful world of Tokenizers.\nSo, uh...", |
|
"Video: 59169985<br>Text: So I hope you enjoyed that whirlwind tour of Google Colab.\nHere's just a little screenshot example o...", |
|
"Video: 60616927<br>Text: It's time for our first LM experiment at this point.\nSo some of this you may know well, you may know...", |
|
"Video: 59673721<br>Text: And here we are in JupyterLab for the last time, and we are looking here at day five, the last day\no...", |
|
"Video: 59508055<br>Text: I'm so very happy that you've reached this epic moment in the course and that you're hanging in ther...", |
|
"Video: 59670259<br>Text: It's remarkable.\nBut you are now at the 95% point.\nThere's 5% remaining of this course.\nUh, maybe it...", |
|
"Video: 60616623<br>Text: So we're now going to start week one of the course when we are going to be looking at exploring fron...", |
|
"Video: 59472383<br>Text: And welcome back to the week six folder.\nWe're now at day two, which is the second and final stage o...", |
|
"Video: 59670171<br>Text: So as the very final step on this part four of day two of week eight, we are now going to build an\ne...", |
|
"Video: 59297721<br>Text: And so now the time has come to talk about the most crucial aspect of Rag, which is the idea of vect...", |
|
"Video: 59297599<br>Text: Well, that was a sneaky detour I took you on in the last one.\nI hope you enjoyed it though, and I ho...", |
|
"Video: 59507635<br>Text: Look, I hope you're excited.\nYou really should be.\nYou've been through 80% of the course and it's al...", |
|
"Video: 59669375<br>Text: Here we are for the day.\n2.1 notebook.\nAnd don't let it be said that I don't ever do anything for yo...", |
|
"Video: 59297733<br>Text: Welcome back to JupyterLab and welcome to your first experiment with the world of Long Chain.\nLet me...", |
|
"Video: 59670369<br>Text: It is terrific that you're hanging on in there and making such great progress with this course.\nAs w...", |
|
"Video: 59166281<br>Text: And with that, amazingly, you completed day one of week two already and that gets you to the 15% poi...", |
|
"Video: 59671567<br>Text: Well, the first thing you're going to notice is that I don't have a notebook open for you.\nAnd that'...", |
|
"Video: 59297593<br>Text: And welcome to continuing our journey with Hrag.\nAnd today it's time to unveil Liang Chen.\nSo first,...", |
|
"Video: 59166461<br>Text: And welcome back to the lab.\nHere we are in Jupyter Lab and we are going to go into week two.\nAnd we...", |
|
"Video: 59167007<br>Text: Well, how fabulous is that?\nI hope that you are as wowed as I am by our new airline, I assistant and...", |
|
"Video: 59508121<br>Text: The moment has arrived.\nHere we go.\nWe're in fine tuning.\nWe do fine tuning.\nTrain.\nThere is also a ...", |
|
"Video: 59295579<br>Text: All right.\nAre you excited to see how this goes?\nLet's give it a try.\nSo in this next section, I cre...", |
|
"Video: 60620375<br>Text: And with that, we've reached an important milestone.\nThe first week of our eight week journey is com...", |
|
"Video: 59472491<br>Text: Welcome back.\nIf you are following along with me in JupyterLab, as I hope you are, then you will nee...", |
|
"Video: 59472425<br>Text: Welcome to week six, day three.\nToday is going to be a day that you will either love or you will hat...", |
|
"Video: 59508057<br>Text: Actually slight change in plan.\nI'm going to wrap up the day.\nDay three at this point, and say that ...", |
|
"Video: 60619577<br>Text: And for the final piece of background information, I wanted to take another moment to talk about API...", |
|
"Video: 59170291<br>Text: Welcome back to Colab and welcome back to our business project.\nSo again our assignment, we are due ...", |
|
"Video: 60619651<br>Text: I mentioned before an AI company called vellum.\nWhen we were talking about the different questions, ...", |
|
"Video: 59473191<br>Text: And you thought we'd never get here.\nHere we are in Jupyter Lab, running our fine tuning for a front...", |
|
"Video: 59170297<br>Text: And here we are in Google Colab, ready for fun with models.\nSo first we do the usual Pip installs an...", |
|
"Video: 59167015<br>Text: Welcome back to Jupyter Lab and welcome to Day Five's Lab.\nAnd this is going to be lots of creativit...", |
|
"Video: 59170043<br>Text: Let me enthusiastically welcome you all back to week three of our LLM engineering journey.\nIf you en...", |
|
"Video: 59473147<br>Text: Well, I'm very relieved.\nI've got that behind me.\nNo more human testing for me.\nWe'll have one final...", |
|
"Video: 59166453<br>Text: Welcome back and welcome to our continuing JupyterLab experience.\nUh, I'm hopefully going to keep yo...", |
|
"Video: 59166915<br>Text: Welcome back to the wonderful world of JupyterLab.\nAnd here we are in week two.\nDay three.\nUh, bring...", |
|
"Video: 59667365<br>Text: Here we are back in Colab, looking at the week seven, day five of the Colab notebooks and I'm on a\nT...", |
|
"Video: 60616845<br>Text: We're on the home stretch.\nThis is the final step in the environment setup, and it's an easy one.\nIt...", |
|
"Video: 59295459<br>Text: And welcome back to More Leaderboard Fest as we go through some more leaderboards.\nBut this time we'...", |
|
"Video: 59471979<br>Text: So we now turn to the parts of the problem, which is perhaps, let's say, not as glamorous as some\nof...", |
|
"Video: 59503705<br>Text: And so now we talk about quantization the q and q Laura.\nQ stands for quantized quantized.\nLaura.\nAn...", |
|
"Video: 59472505<br>Text: So the good news is that this is the very final video about data set curation.\nYou were probably fed...", |
|
"Video: 59669217<br>Text: And welcome to the next part of visualizing the data.\nAnd just very quickly to show it to you in 3D....", |
|
"Video: 59671221<br>Text: I gotta tell you, I don't like to toot my horn a whole lot, but I do think that I've done a great\njo...", |
|
"Video: 59503703<br>Text: Well.\nHello there everybody.\nI am so grateful that you've made it through to the start of week seven...", |
|
"Video: 59473201<br>Text: Well, before we do a postmortem on what happened, let's just quickly look at the standing the rankin...", |
|
"Video: 60622463<br>Text: In this video, we're going to set up a full data science environment for Mac users.\nIn the next vide...", |
|
"Video: 60619299<br>Text: Well, I hope you found that both educational and enjoyable.\nAs we went through and learned so much a...", |
|
"Video: 59295607<br>Text: So to revisit then the solution that we built in the previous day and talk about the metrics.\nAs I s...", |
|
"Video: 59297575<br>Text: Well, welcome to the final part on rag.\nAnd this is the session where you go from being a rag expert...", |
|
"Video: 59507687<br>Text: It's time for action, everybody.\nWe've set up our colab.\nHere we are, week seven, day three.\nWe've g...", |
|
"Video: 59671441<br>Text: And welcome once more to our favorite place to be Jupyter Lab, the Paradise for a data scientist exp...", |
|
"Video: 59673431<br>Text: And here we have it.\nThe user interface is completed.\nThe extra notification came through on my phon...", |
|
"Video: 59473137<br>Text: Let's get straight to it.\nSo the place where you can see everything that's going on and get knee dee...", |
|
"Video: 59166421<br>Text: Welcome back to the radio day in the lab.\nMore to do.\nLet's keep going.\nWhere we left off is we had ...", |
|
"Video: 59295599<br>Text: Welcome to the Jupyter Lab for day four.\nIt's going to look very familiar because it's actually I've...", |
|
"Video: 59669631<br>Text: Here we are in our favorite place to be in JupyterLab, ready for some coding and a lot of coding tha...", |
|
"Video: 59673663<br>Text: But wait, there's more.\nWe need to add some more to the user interface just to make it look more coo...", |
|
"Video: 59506929<br>Text: And we return to the hugging face open LLM leaderboard.\nThe first place you go when selecting your b...", |
|
"Video: 59504785<br>Text: So at this point we're going to talk about hyperparameters.\nAnd we're going to introduce three of th...", |
|
"Video: 59505337<br>Text: So we're now going to look at four bit quantization, the rather remarkable effect of reducing the pr...", |
|
"Video: 59271655<br>Text: So here we are on Hugging Face's main landing page at Hugging Face Core.\nA URL you know.\nWell, since...", |
|
"Video: 59472883<br>Text: Okay, time to reveal the results.\nIt has run to completion.\nAnd here it is.\nSo a moment to pause.\nIt...", |
|
"Video: 59673639<br>Text: And welcome now to the code for our user interface, which we will find in this Python module.\nPrice ...", |
|
"Video: 59472463<br>Text: So last time we looked at a humble linear regression model with feature engineering, and now we say\n...", |
|
"Video: 59297595<br>Text: So by the time you're watching this, hopefully you have played yourself with vectors.\nYou've created...", |
|
"Video: 60619149<br>Text: So we're going to start our exploration into the world of frontier models by playing with the famous...", |
|
"Video: 59297735<br>Text: And at last the time has come to see rag in action.\nAfter all of this talk, and here we are.\nWe're i...", |
|
"Video: 60616407<br>Text: And now over to my Mac people.\nAnd I have news for you.\nIt's exactly the same thing.\nYou go to a fav...", |
|
"Video: 59170235<br>Text: So here we are in Google Colab for our first collaborative session on the cloud using a GPU box.\nOn ...", |
|
"Video: 59472067<br>Text: So we've covered steps 1 to 4 of the five step strategy.\nAnd that brings us to step five, which is p...", |
|
"Video: 59472011<br>Text: Welcome everybody.\nSo in the past I've said quite a few times, I am excited to start this this week ...", |
|
"Video: 59295553<br>Text: Welcome back.\nIn the last part, we gave our GPT four and clawed the challenge of converting a simple...", |
|
"Video: 59297773<br>Text: Well, I hope you're eager with anticipation for this session in JupyterLab as we finally get to see\n...", |
|
"Video: 59295583<br>Text: And here we are back in JupyterLab.\nIt's been a minute.\nWe've been working in Colab for last week, a...", |
|
"Video: 59507329<br>Text: Okay.\nIt's moment of truth time.\nI have just taken our class tester.\nYou remember this class?\nUh, it...", |
|
"Video: 59295429<br>Text: Continuing our investigation of benchmarks, and this will become more real when we actually see some...", |
|
"Video: 60595637<br>Text: Here we are back in the Colab, which has been running overnight for me and probably for you too, I\nh...", |
|
"Video: 59668027<br>Text: And so here we are at the home page for modal.\nAt modal.com spelt model not not model which is confu...", |
|
"Video: 59295527<br>Text: I'm so happy to welcome you to week four, day four on our journey to LLM Engineering and Mastery.\nHe...", |
|
"Video: 59295377<br>Text: Just before we go on to some of the more advanced metrics, I want to mention for a second something\n...", |
|
"Video: 59666211<br>Text: So before we try our new model and one more recap on the models so far and keep notes of this so we\n...", |
|
"Video: 59170107<br>Text: And once again, it's that moment when you take a pause and congratulate yourself on another day of\ns...", |
|
"Video: 60616833<br>Text: So I realized that day one of week one has been a pretty long day, and I assure you that the other,\n...", |
|
"Video: 59472413<br>Text: Wonderful.\nWhere we left off is we had just created the Get Features function, which builds our feat...", |
|
"Video: 59297561<br>Text: And would you believe at this point you're 55% of the way along the journey?\nUh, it's been a while s...", |
|
"Video: 59669211<br>Text: Well, we took on a lot today and we seem to have been successful.\nThese red icons that you see on th...", |
|
"Video: 59166981<br>Text: Welcome to week two, day five.\nThe last day of week two where a lot is coming together.\nI am so grat...", |
|
"Video: 60619227<br>Text: And now let's move to Claude from anthropic, my favorite model and typically the favorite model of\nm...", |
|
"Video: 60620395<br>Text: Welcome back to Jupyter Lab, where I want to show you the assignment, the homework exercise for you\n...", |
|
"Video: 59665127<br>Text: Well hi there everybody.\nI'm not going to give you my usual song and dance about how excited you are...", |
|
"Video: 59668923<br>Text: Well, welcome back to Jupyter Lab for what will be an epic finale to our time in this platform.\nAnd ...", |
|
"Video: 59504887<br>Text: Well, here we are again in Google Colab.\nIt's been a minute since we were here, and welcome back to ...", |
|
"Video: 59170165<br>Text: Welcome, everybody to the last day of week three.\nWeek three.\nDay five.\nWe're here already wrapping ...", |
|
"Video: 60617251<br>Text: Congratulations are definitely in order.\nYesterday was a mammoth first day on this course and you go...", |
|
"Video: 59166951<br>Text: All right, back to the lab.\nBack to our project.\nTime to work with tools.\nI am in the week two folde...", |
|
"Video: 60619619<br>Text: Well, day four was an information dense day.\nI do hope that you learned some something useful here, ...", |
|
"Video: 60616663<br>Text: Well.\nHi there, this is time for PC people to get set up.\nSo all you Mac people out there, you don't...", |
|
"Video: 59508175<br>Text: So I'm taking a moment now to explain that the training costs of optimizing a model for this course\n...", |
|
"Video: 59670087<br>Text: And welcome to part four of day two of week eight.\nUh, there's a lot happening this week, and I have...", |
|
"Video: 59506713<br>Text: Hi everyone.\nSo the reason I'm so fired up about week seven is that this is the time when we actuall...", |
|
"Video: 60620169<br>Text: Hopefully you found this super satisfying to be able to have this nice business result and have it c...", |
|
"Video: 59295435<br>Text: Well, just before we wrap up, let me introduce this week's challenge and talk about what we're going...", |
|
"Video: 59297609<br>Text: Last week, we worked with models that were able to speed up code by a factor of 60,000 times, which\n...", |
|
"Video: 59507489<br>Text: Continuing our adventure through hyperparameters for training.\nThe next one is pretty crucial and it...", |
|
"Video: 59295549<br>Text: And welcome back to our challenge again.\nAnd this time we are working with our beautiful prototype.\n...", |
|
"Video: 59665129<br>Text: And now let me make this real for you by showing you some, some diagrams, particularly now looking\na...", |
|
"Video: 59169991<br>Text: Okay, so that was your introduction to Hugging Face.\nAnd now I'm going to turn to a different resour...", |
|
"Video: 59472027<br>Text: And now the time has come to curate our data set.\nAnd the way we're going to do this is we're going ...", |
|
"Video: 59472307<br>Text: Welcome to week six.\nDay two a day.\nWhen we get back into the data, we look back in anger at our dat...", |
|
"Video: 59508289<br>Text: So here we are now, back in the Colab, in the same one that we kicked off in the previous day.\nIt's ...", |
|
"Video: 59472333<br>Text: Thank you for putting up with me during my foray into traditional machine learning.\nI think it was u...", |
|
"Video: 59295431<br>Text: Now I want to take a quick moment to give you a flyby of five different ways that llms are used comm...", |
|
"Video: 59673449<br>Text: Well, I have to tell you that I'm a little bit sad.\nThis is the beginning of the beginning of the en...", |
|
"Video: 59669389<br>Text: Well.\nHi there.\nSo you've made it to day two of week eight, and I am super grateful that you've been...", |
|
"Video: 59170057<br>Text: And so at the beginning of this week, we started by talking about hugging face pipelines.\nAnd you us...", |
|
"Video: 59166949<br>Text: Welcome back to making chatbots.\nLet's keep going.\nSo for the next part we're going to beef up the s...", |
|
"Video: 59473019<br>Text: Welcome back to an action packed time of of training.\nSo now, after waiting about five minutes when ...", |
|
"Video: 59297585<br>Text: Before we move on, let me show you one more time this fabulous slide that describes the simple three...", |
|
"Video: 59170255<br>Text: And welcome back to us continuing our journey through the model class in Hugging Face Transformers l...", |
|
"Video: 60614589<br>Text: So we're now going to run a large language model directly on your box using a platform called llama,...", |
|
"Video: 59297601<br>Text: I'm not going to lie, at this point you have every reason to be impatient with me.\nWe've been yammer...", |
|
"Video: 60616629<br>Text: And welcome back to team PC and Team Mac as we come back together again for a quick video.\nIn this o...", |
|
"Video: 59297749<br>Text: It's always welcome back to JupyterLab, my favorite place to be.\nAnd now we are, of course in the we...", |
|
"Video: 59170135<br>Text: Welcome.\nIt's week three.\nIt's day four.\nWe are back on the adventure in open source land, back inve...", |
|
"Video: 59472017<br>Text: And this is the first time that we'll be coding against our big project of the course.\nWelcome to Ju...", |
|
"Video: 59507017<br>Text: Welcome to Colab.\nWelcome to the week seven day two Colab.\nAnd just before we try our base model, we...", |
|
"Video: 60619883<br>Text: And now we've arrived at an exciting moment in our first week.\nThe conclusion of the first week is w...", |
|
"Video: 59508297<br>Text: What more is there to say, really?\nTomorrow is the day for results.\nA day that very excited indeed a...", |
|
"Video: 60619247<br>Text: We're going to spend a little bit more time with GPT just to try out a few more interesting things.\n...", |
|
"Video: 59504769<br>Text: Without further ado, we're going to get stuck into it.\nTalking about Laura.\nLow rank adaptation.\nAnd...", |
|
"Video: 59170233<br>Text: Welcome back to our continued exploits with Tokenizers.\nWhat we're now going to look at is what's ca...", |
|
"Video: 59671231<br>Text: And here we are back in the Jupyter Lab for the fast approaching conclusion with a really great proj...", |
|
"Video: 60620397<br>Text: Well, that's a fantastic result to have now arrived towards the end of week one and having completed...", |
|
"Video: 59170093<br>Text: I'm delighted to see you again.\nAs we get started with day three of week three of our adventure and ...", |
|
"Video: 59473089<br>Text: Welcome back.\nSo hopefully you are still impressed by the GPT four mini results.\nThe frontier model ...", |
|
"Video: 60395261<br>Text: Let's keep going with our project to equip our LM with a tool.\nWe just created this piece of code to...", |
|
"Video: 60617259<br>Text: I'm excited to introduce you to your first exercise, and I'm looking forward to seeing what you make...", |
|
"Video: 59507313<br>Text: And it's this time again, when we look at the podium of how our models are performing across the boa...", |
|
"Video: 60619721<br>Text: Now it's time to talk for a minute about tokens.\nTokens are the individual units which get passed in...", |
|
"Video: 59295451<br>Text: I know that everybody.\nIt seems like just the other day that we were embarking on our quest together...", |
|
"Video: 59166919<br>Text: And with that, it concludes our session on tools.\nAnd at this point, you are probably an expert on t...", |
|
"Video: 59295441<br>Text: Okay, so welcome to our leaderboard fast as we go through a ton of essential leaderboards for your\nc...", |
|
"Video: 59295541<br>Text: And welcome back.\nYou've just seen GPT four zero spectacularly failed to work on our hard Python con...", |
|
"Video: 59473101<br>Text: Welcome back.\nSo about ten minutes later, maybe 15 minutes later, the run has completed.\nAnd how do ...", |
|
"Video: 59507423<br>Text: So you may remember eons ago when we were building our data set.\nAt the end of that, we uploaded our...", |
|
"Video: 59295545<br>Text: I really hope you've enjoyed this week.\nWe've got tons done.\nWe've experimented with all sorts of ne...", |
|
"Video: 59472503<br>Text: Welcome back to Jupyter Lab.\nLast time, we looked at some silly models for predicting the price of p...", |
|
"Video: 60614591<br>Text: The mantra of this course is that the best way to learn is by doing, and we will be doing stuff toge...", |
|
"Video: 59473021<br>Text: Welcome to our favorite place to be to JupyterLab.\nHere we are again now in day three.\nIn week six.\n...", |
|
"Video: 60617255<br>Text: I'm now going to talk for a bit about models.\nA term you often hear is the term frontier models, whi...", |
|
"Video: 59667829<br>Text: Well.\nHello there.\nLook, I know what you're thinking.\nYou're thinking I peaked too early.\nLast week ...", |
|
"Video: 59505329<br>Text: Welcome back.\nYou may, like me, have just gone off and got a coffee while things loaded back up agai...", |
|
"Video: 59669049<br>Text: So what you just saw was an ephemeral app, as it's called, which means just a temporary app that you...", |
|
"Video: 60619439<br>Text: This now brings us to an extremely important property of LMS called the context window that I want t...", |
|
"Video: 59668181<br>Text: And so it gives me great pleasure to introduce to you the project that I've lined up for you this we...", |
|
"Video: 59472441<br>Text: Welcome back.\nSo we've been doing the thoroughly distasteful, unsavory work of feature engineering.\n...", |
|
"Video: 59507785<br>Text: Well, I'm sure you're fed up of me saying that the moment of truth has arrived, but it really has.\nT...", |
|
"Video: 59295587<br>Text: When I left you, we had just created this simple user interface for converting from Python to C plus...", |
|
"Video: 59166465<br>Text: Welcome back to the JupyterLab on Gradio day, so you'll remember where we left off.\nWe'd written two...", |
|
"Video: 59473071<br>Text: Hey, gang.\nLook, I know what you're thinking.\nThis week was supposed to be training week.\nI set it a...", |
|
"Video: 59295423<br>Text: Welcome to day two of week four, when we get more into leaderboards so that by the end of this, you'...", |
|
"Video: 59297723<br>Text: So I know what you're thinking.\nYou're thinking, what's going on here?\nWe're on day five.\nWe're on d...", |
|
"Video: 59166947<br>Text: Well, thank you for coming along for week two, day four.\nWe have lots of good stuff in store today.\n...", |
|
"Video: 59666831<br>Text: Take one more moment to look at this very nice diagram that lays it all out, and we will move on.\nNo...", |
|
"Video: 59295493<br>Text: And welcome to week four, day three.\nAs we are about to embark upon another business project which w...", |
|
"Video: 60616855<br>Text: Now I know what you're thinking.\nWe've been building environments for so long.\nAre we not done yet?\n...", |
|
"Video: 59506611<br>Text: So in a future day, I'm going to be training, fine tuning a model and creating a fine tuned model.\nA...", |
|
"Video: 60616493<br>Text: I'll just take a quick moment to introduce myself to convince you that I am actually qualified to be...", |
|
"Video: 59166317<br>Text: And welcome to week two, day two, as we continue our adventure into the realm of LMS.\nUh, so today, ...", |
|
"Video: 59295439<br>Text: So I'm aware that there's a big risk that you are getting fed up of leaderboards, because we've done...", |
|
"Video: 59472421<br>Text: And welcome back to our final time in Jupyter Lab with traditional machine learning.\nIt's almost ove...", |
|
"Video: 59472137<br>Text: Well, well, well, it's been a long day, but congratulations, you've made it.\nWe've gone through and ...", |
|
"Video: 59297693<br>Text: So at the end of each week, it's customary for me to give you a challenge, an assignment to do on\nyo...", |
|
"Video: 60620143<br>Text: So we're going to make a call to GPT four.\nOh, that's going to ask it to look through a set of links...", |
|
"Video: 60619501<br>Text: I welcome to day four of our time together.\nThis is a very important day.\nToday we're going to be lo...", |
|
"Video: 59297743<br>Text: And welcome to day five.\nFor reals.\nWe're actually in the proper Jupyter notebook.\nThis time we're i...", |
|
"Video: 59166847<br>Text: Well, they say that time flies when you're having fun, and it certainly feels like time is flying.\nU...", |
|
"Video: 59170223<br>Text: Well.\nFantastic.\nIt's coming up to the end of the week, and that means it's coming up to a challenge...", |
|
"Video: 59170037<br>Text: So how does it feel to be 30% of the way down the journey to being a proficient LLM engineer?\nTake a...", |
|
"Video: 59295609<br>Text: You must be feeling absolutely exhausted at this point.\nAnd if you are, that is okay.\nYou have done ...", |
|
"Video: 60619281<br>Text: Well, I'm delighted to welcome you to day three of our eight week journey together.\nAnd today we're ...", |
|
"Video: 59472429<br>Text: And continuing on our strategy to solve commercial problems with LMS, we get to step four, which is\n...", |
|
"Video: 59167009<br>Text: Welcome back.\nIt's time to make our full agent framework.\nI'm super excited about this.\nIt's pulling...", |
|
"Video: 59166481<br>Text: And here, once more we find ourselves in our favorite place, the Jupyter Lab.\nReady to go with weeks...", |
|
"Video: 59670933<br>Text: I realized my enthusiasm for this project is a bit insane, but I have to tell you that I am very sat...", |
|
"Video: 59670073<br>Text: Okay, it's time to complete the Rag workflow in our Jupyter Lab on day 2.3.\nWe've got this function ...", |
|
"Video: 59673595<br>Text: That concludes a mammoth project.\nThree weeks in the making.\nIn the course of those three weeks, sta...", |
|
"Video: 59297603<br>Text: And I'm delighted to welcome you back to LM engineering on the day that we turn to vectors.\nFinally,...", |
|
"Video: 60614541<br>Text: I am delighted to welcome you to the first day of our eight weeks together as you join me on this ad...", |
|
"Video: 59667357<br>Text: Let's now see our results side by side.\nWe started our journey with a constant model that was at $1....", |
|
"Video: 59667841<br>Text: Now, look, I know that I went through that very fast, but maybe, uh, you're still, uh, blinking\nat t...", |
|
"Video: 59472007<br>Text: So I hope you enjoyed our first bash at Scrubbing Data, and that you are now looking through the cod...", |
|
"Video: 59507435<br>Text: So I'm now going to talk about five important hyperparameters for the training process.\nAnd some of ...", |
|
"Video: 59509185<br>Text: So this is where I left you looking at this satisfying chart on training loss and seeing the trainin...", |
|
"Video: 59473159<br>Text: Welcome to Jupyter Lab and welcome to our experiments at the frontier.\nSo we are going to put our fr...", |
|
"Video: 60619447<br>Text: I want to take a moment to talk about something that's very fundamental to an LLM, which is the numb...", |
|
"Video: 59166353<br>Text: Well, congratulations on leveling up yet again.\nYou've got some real hard skills that you've added t...", |
|
"Video: 60619123<br>Text: So what we're now going to do is we're going to look at some models in practice and start to compare...", |
|
"Video: 59295363<br>Text: Well, another congratulations moment.\nYou have 40% on the way to being an LM engineer at a high leve...", |
|
"Video: 60619289<br>Text: And now we'll go a bit faster through the other models.\nWe'll start with Google's Gemini.\nI have the...", |
|
"Video: 59472873<br>Text: So it's quite an adventure that we had at the frontier of what's capable with Llms today, solving a\n...", |
|
"Video: 60619429<br>Text: Let me talk about some other phenomena that have happened over the last few years.\nOne of them has b...", |
|
"Video: 59295601<br>Text: So it's time to continue our journey into the world of open source and understand which models we sh...", |
|
"Video: 59170025<br>Text: And a massive welcome back one more time to LM engineering.\nWe are in week three, day two and we are...", |
|
"Video: 59166443<br>Text: And welcome back everybody.\nWelcome to week two day three.\nIt's a continuation of our enjoyment of r...", |
|
"Video: 60620025<br>Text: And welcome back to Jupyter Lab, one of my very favorite places to be.\nWhen Jupyter Lab sprung up on...", |
|
"Video: 59170055<br>Text: Welcome to the world of Google Colab.\nYou may already be very familiar with Google Colab, even if so..." |
|
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59506507\\u003cbr\\u003eText: Well, I realized that was a whole lot of theory, but I hope it gave you a good intuition that will\\nb...\",\"Video: 59671315\\u003cbr\\u003eText: Okay, so here we are, back in Jupyter Lab, ready for the next use of a frontier model, and see this\\n...\",\"Video: 60616895\\u003cbr\\u003eText: It feels like 100 videos ago that I told you that we were going to have instant gratification with o...\",\"Video: 60619275\\u003cbr\\u003eText: And we will conclude our expedition into the world of frontier models through their chat interface b...\",\"Video: 59472693\\u003cbr\\u003eText: Friends.\\nI am absolutely exhausted.\\nI am exhausted and a little tiny bit traumatized.\\nAnd you are so...\",\"Video: 59670121\\u003cbr\\u003eText: So it's business time right now.\\nWe are going to build a Rag pipeline to estimate the price of produ...\",\"Video: 59295619\\u003cbr\\u003eText: Welcome back to the the moment when we bring it all together into a beautiful user interface.\\nBut fi...\",\"Video: 60617163\\u003cbr\\u003eText: And already that wraps up day two.\\nNow that you have built that solution.\\nAnd congratulations on tha...\",\"Video: 60616423\\u003cbr\\u003eText: So I hope you've just enjoyed yourself experimenting with different LMS locally on your box using th...\",\"Video: 59170227\\u003cbr\\u003eText: Welcome back to Google Colab.\\nHere we are ready to explore the wonderful world of Tokenizers.\\nSo, uh...\",\"Video: 59169985\\u003cbr\\u003eText: So I hope you enjoyed that whirlwind tour of Google Colab.\\nHere's just a little screenshot example o...\",\"Video: 60616927\\u003cbr\\u003eText: It's time for our first LM experiment at this point.\\nSo some of this you may know well, you may know...\",\"Video: 59673721\\u003cbr\\u003eText: And here we are in JupyterLab for the last time, and we are looking here at day five, the last day\\no...\",\"Video: 59508055\\u003cbr\\u003eText: I'm so very happy that you've reached this epic moment in the course and that you're hanging in ther...\",\"Video: 59670259\\u003cbr\\u003eText: It's remarkable.\\nBut you are now at the 95% point.\\nThere's 5% remaining of this course.\\nUh, maybe it...\",\"Video: 60616623\\u003cbr\\u003eText: So we're now going to start week one of the course when we are going to be looking at exploring fron...\",\"Video: 59472383\\u003cbr\\u003eText: And welcome back to the week six folder.\\nWe're now at day two, which is the second and final stage o...\",\"Video: 59670171\\u003cbr\\u003eText: So as the very final step on this part four of day two of week eight, we are now going to build an\\ne...\",\"Video: 59297721\\u003cbr\\u003eText: And so now the time has come to talk about the most crucial aspect of Rag, which is the idea of vect...\",\"Video: 59297599\\u003cbr\\u003eText: Well, that was a sneaky detour I took you on in the last one.\\nI hope you enjoyed it though, and I ho...\",\"Video: 59507635\\u003cbr\\u003eText: Look, I hope you're excited.\\nYou really should be.\\nYou've been through 80% of the course and it's al...\",\"Video: 59669375\\u003cbr\\u003eText: Here we are for the day.\\n2.1 notebook.\\nAnd don't let it be said that I don't ever do anything for yo...\",\"Video: 59297733\\u003cbr\\u003eText: Welcome back to JupyterLab and welcome to your first experiment with the world of Long Chain.\\nLet me...\",\"Video: 59670369\\u003cbr\\u003eText: It is terrific that you're hanging on in there and making such great progress with this course.\\nAs w...\",\"Video: 59166281\\u003cbr\\u003eText: And with that, amazingly, you completed day one of week two already and that gets you to the 15% poi...\",\"Video: 59671567\\u003cbr\\u003eText: Well, the first thing you're going to notice is that I don't have a notebook open for you.\\nAnd that'...\",\"Video: 59297593\\u003cbr\\u003eText: And welcome to continuing our journey with Hrag.\\nAnd today it's time to unveil Liang Chen.\\nSo first,...\",\"Video: 59166461\\u003cbr\\u003eText: And welcome back to the lab.\\nHere we are in Jupyter Lab and we are going to go into week two.\\nAnd we...\",\"Video: 59167007\\u003cbr\\u003eText: Well, how fabulous is that?\\nI hope that you are as wowed as I am by our new airline, I assistant and...\",\"Video: 59508121\\u003cbr\\u003eText: The moment has arrived.\\nHere we go.\\nWe're in fine tuning.\\nWe do fine tuning.\\nTrain.\\nThere is also a ...\",\"Video: 59295579\\u003cbr\\u003eText: All right.\\nAre you excited to see how this goes?\\nLet's give it a try.\\nSo in this next section, I cre...\",\"Video: 60620375\\u003cbr\\u003eText: And with that, we've reached an important milestone.\\nThe first week of our eight week journey is com...\",\"Video: 59472491\\u003cbr\\u003eText: Welcome back.\\nIf you are following along with me in JupyterLab, as I hope you are, then you will nee...\",\"Video: 59472425\\u003cbr\\u003eText: Welcome to week six, day three.\\nToday is going to be a day that you will either love or you will hat...\",\"Video: 59508057\\u003cbr\\u003eText: Actually slight change in plan.\\nI'm going to wrap up the day.\\nDay three at this point, and say that ...\",\"Video: 60619577\\u003cbr\\u003eText: And for the final piece of background information, I wanted to take another moment to talk about API...\",\"Video: 59170291\\u003cbr\\u003eText: Welcome back to Colab and welcome back to our business project.\\nSo again our assignment, we are due ...\",\"Video: 60619651\\u003cbr\\u003eText: I mentioned before an AI company called vellum.\\nWhen we were talking about the different questions, ...\",\"Video: 59473191\\u003cbr\\u003eText: And you thought we'd never get here.\\nHere we are in Jupyter Lab, running our fine tuning for a front...\",\"Video: 59170297\\u003cbr\\u003eText: And here we are in Google Colab, ready for fun with models.\\nSo first we do the usual Pip installs an...\",\"Video: 59167015\\u003cbr\\u003eText: Welcome back to Jupyter Lab and welcome to Day Five's Lab.\\nAnd this is going to be lots of creativit...\",\"Video: 59170043\\u003cbr\\u003eText: Let me enthusiastically welcome you all back to week three of our LLM engineering journey.\\nIf you en...\",\"Video: 59473147\\u003cbr\\u003eText: Well, I'm very relieved.\\nI've got that behind me.\\nNo more human testing for me.\\nWe'll have one final...\",\"Video: 59166453\\u003cbr\\u003eText: Welcome back and welcome to our continuing JupyterLab experience.\\nUh, I'm hopefully going to keep yo...\",\"Video: 59166915\\u003cbr\\u003eText: Welcome back to the wonderful world of JupyterLab.\\nAnd here we are in week two.\\nDay three.\\nUh, bring...\",\"Video: 59667365\\u003cbr\\u003eText: Here we are back in Colab, looking at the week seven, day five of the Colab notebooks and I'm on a\\nT...\",\"Video: 60616845\\u003cbr\\u003eText: We're on the home stretch.\\nThis is the final step in the environment setup, and it's an easy one.\\nIt...\",\"Video: 59295459\\u003cbr\\u003eText: And welcome back to More Leaderboard Fest as we go through some more leaderboards.\\nBut this time we'...\",\"Video: 59471979\\u003cbr\\u003eText: So we now turn to the parts of the problem, which is perhaps, let's say, not as glamorous as some\\nof...\",\"Video: 59503705\\u003cbr\\u003eText: And so now we talk about quantization the q and q Laura.\\nQ stands for quantized quantized.\\nLaura.\\nAn...\",\"Video: 59472505\\u003cbr\\u003eText: So the good news is that this is the very final video about data set curation.\\nYou were probably fed...\",\"Video: 59669217\\u003cbr\\u003eText: And welcome to the next part of visualizing the data.\\nAnd just very quickly to show it to you in 3D....\",\"Video: 59671221\\u003cbr\\u003eText: I gotta tell you, I don't like to toot my horn a whole lot, but I do think that I've done a great\\njo...\",\"Video: 59503703\\u003cbr\\u003eText: Well.\\nHello there everybody.\\nI am so grateful that you've made it through to the start of week seven...\",\"Video: 59473201\\u003cbr\\u003eText: Well, before we do a postmortem on what happened, let's just quickly look at the standing the rankin...\",\"Video: 60622463\\u003cbr\\u003eText: In this video, we're going to set up a full data science environment for Mac users.\\nIn the next vide...\",\"Video: 60619299\\u003cbr\\u003eText: Well, I hope you found that both educational and enjoyable.\\nAs we went through and learned so much a...\",\"Video: 59295607\\u003cbr\\u003eText: So to revisit then the solution that we built in the previous day and talk about the metrics.\\nAs I s...\",\"Video: 59297575\\u003cbr\\u003eText: Well, welcome to the final part on rag.\\nAnd this is the session where you go from being a rag expert...\",\"Video: 59507687\\u003cbr\\u003eText: It's time for action, everybody.\\nWe've set up our colab.\\nHere we are, week seven, day three.\\nWe've g...\",\"Video: 59671441\\u003cbr\\u003eText: And welcome once more to our favorite place to be Jupyter Lab, the Paradise for a data scientist exp...\",\"Video: 59673431\\u003cbr\\u003eText: And here we have it.\\nThe user interface is completed.\\nThe extra notification came through on my phon...\",\"Video: 59473137\\u003cbr\\u003eText: Let's get straight to it.\\nSo the place where you can see everything that's going on and get knee dee...\",\"Video: 59166421\\u003cbr\\u003eText: Welcome back to the radio day in the lab.\\nMore to do.\\nLet's keep going.\\nWhere we left off is we had ...\",\"Video: 59295599\\u003cbr\\u003eText: Welcome to the Jupyter Lab for day four.\\nIt's going to look very familiar because it's actually I've...\",\"Video: 59669631\\u003cbr\\u003eText: Here we are in our favorite place to be in JupyterLab, ready for some coding and a lot of coding tha...\",\"Video: 59673663\\u003cbr\\u003eText: But wait, there's more.\\nWe need to add some more to the user interface just to make it look more coo...\",\"Video: 59506929\\u003cbr\\u003eText: And we return to the hugging face open LLM leaderboard.\\nThe first place you go when selecting your b...\",\"Video: 59504785\\u003cbr\\u003eText: So at this point we're going to talk about hyperparameters.\\nAnd we're going to introduce three of th...\",\"Video: 59505337\\u003cbr\\u003eText: So we're now going to look at four bit quantization, the rather remarkable effect of reducing the pr...\",\"Video: 59271655\\u003cbr\\u003eText: So here we are on Hugging Face's main landing page at Hugging Face Core.\\nA URL you know.\\nWell, since...\",\"Video: 59472883\\u003cbr\\u003eText: Okay, time to reveal the results.\\nIt has run to completion.\\nAnd here it is.\\nSo a moment to pause.\\nIt...\",\"Video: 59673639\\u003cbr\\u003eText: And welcome now to the code for our user interface, which we will find in this Python module.\\nPrice ...\",\"Video: 59472463\\u003cbr\\u003eText: So last time we looked at a humble linear regression model with feature engineering, and now we say\\n...\",\"Video: 59297595\\u003cbr\\u003eText: So by the time you're watching this, hopefully you have played yourself with vectors.\\nYou've created...\",\"Video: 60619149\\u003cbr\\u003eText: So we're going to start our exploration into the world of frontier models by playing with the famous...\",\"Video: 59297735\\u003cbr\\u003eText: And at last the time has come to see rag in action.\\nAfter all of this talk, and here we are.\\nWe're i...\",\"Video: 60616407\\u003cbr\\u003eText: And now over to my Mac people.\\nAnd I have news for you.\\nIt's exactly the same thing.\\nYou go to a fav...\",\"Video: 59170235\\u003cbr\\u003eText: So here we are in Google Colab for our first collaborative session on the cloud using a GPU box.\\nOn ...\",\"Video: 59472067\\u003cbr\\u003eText: So we've covered steps 1 to 4 of the five step strategy.\\nAnd that brings us to step five, which is p...\",\"Video: 59472011\\u003cbr\\u003eText: Welcome everybody.\\nSo in the past I've said quite a few times, I am excited to start this this week ...\",\"Video: 59295553\\u003cbr\\u003eText: Welcome back.\\nIn the last part, we gave our GPT four and clawed the challenge of converting a simple...\",\"Video: 59297773\\u003cbr\\u003eText: Well, I hope you're eager with anticipation for this session in JupyterLab as we finally get to see\\n...\",\"Video: 59295583\\u003cbr\\u003eText: And here we are back in JupyterLab.\\nIt's been a minute.\\nWe've been working in Colab for last week, a...\",\"Video: 59507329\\u003cbr\\u003eText: Okay.\\nIt's moment of truth time.\\nI have just taken our class tester.\\nYou remember this class?\\nUh, it...\",\"Video: 59295429\\u003cbr\\u003eText: Continuing our investigation of benchmarks, and this will become more real when we actually see some...\",\"Video: 60595637\\u003cbr\\u003eText: Here we are back in the Colab, which has been running overnight for me and probably for you too, I\\nh...\",\"Video: 59668027\\u003cbr\\u003eText: And so here we are at the home page for modal.\\nAt modal.com spelt model not not model which is confu...\",\"Video: 59295527\\u003cbr\\u003eText: I'm so happy to welcome you to week four, day four on our journey to LLM Engineering and Mastery.\\nHe...\",\"Video: 59295377\\u003cbr\\u003eText: Just before we go on to some of the more advanced metrics, I want to mention for a second something\\n...\",\"Video: 59666211\\u003cbr\\u003eText: So before we try our new model and one more recap on the models so far and keep notes of this so we\\n...\",\"Video: 59170107\\u003cbr\\u003eText: And once again, it's that moment when you take a pause and congratulate yourself on another day of\\ns...\",\"Video: 60616833\\u003cbr\\u003eText: So I realized that day one of week one has been a pretty long day, and I assure you that the other,\\n...\",\"Video: 59472413\\u003cbr\\u003eText: Wonderful.\\nWhere we left off is we had just created the Get Features function, which builds our feat...\",\"Video: 59297561\\u003cbr\\u003eText: And would you believe at this point you're 55% of the way along the journey?\\nUh, it's been a while s...\",\"Video: 59669211\\u003cbr\\u003eText: Well, we took on a lot today and we seem to have been successful.\\nThese red icons that you see on th...\",\"Video: 59166981\\u003cbr\\u003eText: Welcome to week two, day five.\\nThe last day of week two where a lot is coming together.\\nI am so grat...\",\"Video: 60619227\\u003cbr\\u003eText: And now let's move to Claude from anthropic, my favorite model and typically the favorite model of\\nm...\",\"Video: 60620395\\u003cbr\\u003eText: Welcome back to Jupyter Lab, where I want to show you the assignment, the homework exercise for you\\n...\",\"Video: 59665127\\u003cbr\\u003eText: Well hi there everybody.\\nI'm not going to give you my usual song and dance about how excited you are...\",\"Video: 59668923\\u003cbr\\u003eText: Well, welcome back to Jupyter Lab for what will be an epic finale to our time in this platform.\\nAnd ...\",\"Video: 59504887\\u003cbr\\u003eText: Well, here we are again in Google Colab.\\nIt's been a minute since we were here, and welcome back to ...\",\"Video: 59170165\\u003cbr\\u003eText: Welcome, everybody to the last day of week three.\\nWeek three.\\nDay five.\\nWe're here already wrapping ...\",\"Video: 60617251\\u003cbr\\u003eText: Congratulations are definitely in order.\\nYesterday was a mammoth first day on this course and you go...\",\"Video: 59166951\\u003cbr\\u003eText: All right, back to the lab.\\nBack to our project.\\nTime to work with tools.\\nI am in the week two folde...\",\"Video: 60619619\\u003cbr\\u003eText: Well, day four was an information dense day.\\nI do hope that you learned some something useful here, ...\",\"Video: 60616663\\u003cbr\\u003eText: Well.\\nHi there, this is time for PC people to get set up.\\nSo all you Mac people out there, you don't...\",\"Video: 59508175\\u003cbr\\u003eText: So I'm taking a moment now to explain that the training costs of optimizing a model for this course\\n...\",\"Video: 59670087\\u003cbr\\u003eText: And welcome to part four of day two of week eight.\\nUh, there's a lot happening this week, and I have...\",\"Video: 59506713\\u003cbr\\u003eText: Hi everyone.\\nSo the reason I'm so fired up about week seven is that this is the time when we actuall...\",\"Video: 60620169\\u003cbr\\u003eText: Hopefully you found this super satisfying to be able to have this nice business result and have it c...\",\"Video: 59295435\\u003cbr\\u003eText: Well, just before we wrap up, let me introduce this week's challenge and talk about what we're going...\",\"Video: 59297609\\u003cbr\\u003eText: Last week, we worked with models that were able to speed up code by a factor of 60,000 times, which\\n...\",\"Video: 59507489\\u003cbr\\u003eText: Continuing our adventure through hyperparameters for training.\\nThe next one is pretty crucial and it...\",\"Video: 59295549\\u003cbr\\u003eText: And welcome back to our challenge again.\\nAnd this time we are working with our beautiful prototype.\\n...\",\"Video: 59665129\\u003cbr\\u003eText: And now let me make this real for you by showing you some, some diagrams, particularly now looking\\na...\",\"Video: 59169991\\u003cbr\\u003eText: Okay, so that was your introduction to Hugging Face.\\nAnd now I'm going to turn to a different resour...\",\"Video: 59472027\\u003cbr\\u003eText: And now the time has come to curate our data set.\\nAnd the way we're going to do this is we're going ...\",\"Video: 59472307\\u003cbr\\u003eText: Welcome to week six.\\nDay two a day.\\nWhen we get back into the data, we look back in anger at our dat...\",\"Video: 59508289\\u003cbr\\u003eText: So here we are now, back in the Colab, in the same one that we kicked off in the previous day.\\nIt's ...\",\"Video: 59472333\\u003cbr\\u003eText: Thank you for putting up with me during my foray into traditional machine learning.\\nI think it was u...\",\"Video: 59295431\\u003cbr\\u003eText: Now I want to take a quick moment to give you a flyby of five different ways that llms are used comm...\",\"Video: 59673449\\u003cbr\\u003eText: Well, I have to tell you that I'm a little bit sad.\\nThis is the beginning of the beginning of the en...\",\"Video: 59669389\\u003cbr\\u003eText: Well.\\nHi there.\\nSo you've made it to day two of week eight, and I am super grateful that you've been...\",\"Video: 59170057\\u003cbr\\u003eText: And so at the beginning of this week, we started by talking about hugging face pipelines.\\nAnd you us...\",\"Video: 59166949\\u003cbr\\u003eText: Welcome back to making chatbots.\\nLet's keep going.\\nSo for the next part we're going to beef up the s...\",\"Video: 59473019\\u003cbr\\u003eText: Welcome back to an action packed time of of training.\\nSo now, after waiting about five minutes when ...\",\"Video: 59297585\\u003cbr\\u003eText: Before we move on, let me show you one more time this fabulous slide that describes the simple three...\",\"Video: 59170255\\u003cbr\\u003eText: And welcome back to us continuing our journey through the model class in Hugging Face Transformers l...\",\"Video: 60614589\\u003cbr\\u003eText: So we're now going to run a large language model directly on your box using a platform called llama,...\",\"Video: 59297601\\u003cbr\\u003eText: I'm not going to lie, at this point you have every reason to be impatient with me.\\nWe've been yammer...\",\"Video: 60616629\\u003cbr\\u003eText: And welcome back to team PC and Team Mac as we come back together again for a quick video.\\nIn this o...\",\"Video: 59297749\\u003cbr\\u003eText: It's always welcome back to JupyterLab, my favorite place to be.\\nAnd now we are, of course in the we...\",\"Video: 59170135\\u003cbr\\u003eText: Welcome.\\nIt's week three.\\nIt's day four.\\nWe are back on the adventure in open source land, back inve...\",\"Video: 59472017\\u003cbr\\u003eText: And this is the first time that we'll be coding against our big project of the course.\\nWelcome to Ju...\",\"Video: 59507017\\u003cbr\\u003eText: Welcome to Colab.\\nWelcome to the week seven day two Colab.\\nAnd just before we try our base model, we...\",\"Video: 60619883\\u003cbr\\u003eText: And now we've arrived at an exciting moment in our first week.\\nThe conclusion of the first week is w...\",\"Video: 59508297\\u003cbr\\u003eText: What more is there to say, really?\\nTomorrow is the day for results.\\nA day that very excited indeed a...\",\"Video: 60619247\\u003cbr\\u003eText: We're going to spend a little bit more time with GPT just to try out a few more interesting things.\\n...\",\"Video: 59504769\\u003cbr\\u003eText: Without further ado, we're going to get stuck into it.\\nTalking about Laura.\\nLow rank adaptation.\\nAnd...\",\"Video: 59170233\\u003cbr\\u003eText: Welcome back to our continued exploits with Tokenizers.\\nWhat we're now going to look at is what's ca...\",\"Video: 59671231\\u003cbr\\u003eText: And here we are back in the Jupyter Lab for the fast approaching conclusion with a really great proj...\",\"Video: 60620397\\u003cbr\\u003eText: Well, that's a fantastic result to have now arrived towards the end of week one and having completed...\",\"Video: 59170093\\u003cbr\\u003eText: I'm delighted to see you again.\\nAs we get started with day three of week three of our adventure and ...\",\"Video: 59473089\\u003cbr\\u003eText: Welcome back.\\nSo hopefully you are still impressed by the GPT four mini results.\\nThe frontier model ...\",\"Video: 60395261\\u003cbr\\u003eText: Let's keep going with our project to equip our LM with a tool.\\nWe just created this piece of code to...\",\"Video: 60617259\\u003cbr\\u003eText: I'm excited to introduce you to your first exercise, and I'm looking forward to seeing what you make...\",\"Video: 59507313\\u003cbr\\u003eText: And it's this time again, when we look at the podium of how our models are performing across the boa...\",\"Video: 60619721\\u003cbr\\u003eText: Now it's time to talk for a minute about tokens.\\nTokens are the individual units which get passed in...\",\"Video: 59295451\\u003cbr\\u003eText: I know that everybody.\\nIt seems like just the other day that we were embarking on our quest together...\",\"Video: 59166919\\u003cbr\\u003eText: And with that, it concludes our session on tools.\\nAnd at this point, you are probably an expert on t...\",\"Video: 59295441\\u003cbr\\u003eText: Okay, so welcome to our leaderboard fast as we go through a ton of essential leaderboards for your\\nc...\",\"Video: 59295541\\u003cbr\\u003eText: And welcome back.\\nYou've just seen GPT four zero spectacularly failed to work on our hard Python con...\",\"Video: 59473101\\u003cbr\\u003eText: Welcome back.\\nSo about ten minutes later, maybe 15 minutes later, the run has completed.\\nAnd how do ...\",\"Video: 59507423\\u003cbr\\u003eText: So you may remember eons ago when we were building our data set.\\nAt the end of that, we uploaded our...\",\"Video: 59295545\\u003cbr\\u003eText: I really hope you've enjoyed this week.\\nWe've got tons done.\\nWe've experimented with all sorts of ne...\",\"Video: 59472503\\u003cbr\\u003eText: Welcome back to Jupyter Lab.\\nLast time, we looked at some silly models for predicting the price of p...\",\"Video: 60614591\\u003cbr\\u003eText: The mantra of this course is that the best way to learn is by doing, and we will be doing stuff toge...\",\"Video: 59473021\\u003cbr\\u003eText: Welcome to our favorite place to be to JupyterLab.\\nHere we are again now in day three.\\nIn week six.\\n...\",\"Video: 60617255\\u003cbr\\u003eText: I'm now going to talk for a bit about models.\\nA term you often hear is the term frontier models, whi...\",\"Video: 59667829\\u003cbr\\u003eText: Well.\\nHello there.\\nLook, I know what you're thinking.\\nYou're thinking I peaked too early.\\nLast week ...\",\"Video: 59505329\\u003cbr\\u003eText: Welcome back.\\nYou may, like me, have just gone off and got a coffee while things loaded back up agai...\",\"Video: 59669049\\u003cbr\\u003eText: So what you just saw was an ephemeral app, as it's called, which means just a temporary app that you...\",\"Video: 60619439\\u003cbr\\u003eText: This now brings us to an extremely important property of LMS called the context window that I want t...\",\"Video: 59668181\\u003cbr\\u003eText: And so it gives me great pleasure to introduce to you the project that I've lined up for you this we...\",\"Video: 59472441\\u003cbr\\u003eText: Welcome back.\\nSo we've been doing the thoroughly distasteful, unsavory work of feature engineering.\\n...\",\"Video: 59507785\\u003cbr\\u003eText: Well, I'm sure you're fed up of me saying that the moment of truth has arrived, but it really has.\\nT...\",\"Video: 59295587\\u003cbr\\u003eText: When I left you, we had just created this simple user interface for converting from Python to C plus...\",\"Video: 59166465\\u003cbr\\u003eText: Welcome back to the JupyterLab on Gradio day, so you'll remember where we left off.\\nWe'd written two...\",\"Video: 59473071\\u003cbr\\u003eText: Hey, gang.\\nLook, I know what you're thinking.\\nThis week was supposed to be training week.\\nI set it a...\",\"Video: 59295423\\u003cbr\\u003eText: Welcome to day two of week four, when we get more into leaderboards so that by the end of this, you'...\",\"Video: 59297723\\u003cbr\\u003eText: So I know what you're thinking.\\nYou're thinking, what's going on here?\\nWe're on day five.\\nWe're on d...\",\"Video: 59166947\\u003cbr\\u003eText: Well, thank you for coming along for week two, day four.\\nWe have lots of good stuff in store today.\\n...\",\"Video: 59666831\\u003cbr\\u003eText: Take one more moment to look at this very nice diagram that lays it all out, and we will move on.\\nNo...\",\"Video: 59295493\\u003cbr\\u003eText: And welcome to week four, day three.\\nAs we are about to embark upon another business project which w...\",\"Video: 60616855\\u003cbr\\u003eText: Now I know what you're thinking.\\nWe've been building environments for so long.\\nAre we not done yet?\\n...\",\"Video: 59506611\\u003cbr\\u003eText: So in a future day, I'm going to be training, fine tuning a model and creating a fine tuned model.\\nA...\",\"Video: 60616493\\u003cbr\\u003eText: I'll just take a quick moment to introduce myself to convince you that I am actually qualified to be...\",\"Video: 59166317\\u003cbr\\u003eText: And welcome to week two, day two, as we continue our adventure into the realm of LMS.\\nUh, so today, ...\",\"Video: 59295439\\u003cbr\\u003eText: So I'm aware that there's a big risk that you are getting fed up of leaderboards, because we've done...\",\"Video: 59472421\\u003cbr\\u003eText: And welcome back to our final time in Jupyter Lab with traditional machine learning.\\nIt's almost ove...\",\"Video: 59472137\\u003cbr\\u003eText: Well, well, well, it's been a long day, but congratulations, you've made it.\\nWe've gone through and ...\",\"Video: 59297693\\u003cbr\\u003eText: So at the end of each week, it's customary for me to give you a challenge, an assignment to do on\\nyo...\",\"Video: 60620143\\u003cbr\\u003eText: So we're going to make a call to GPT four.\\nOh, that's going to ask it to look through a set of links...\",\"Video: 60619501\\u003cbr\\u003eText: I welcome to day four of our time together.\\nThis is a very important day.\\nToday we're going to be lo...\",\"Video: 59297743\\u003cbr\\u003eText: And welcome to day five.\\nFor reals.\\nWe're actually in the proper Jupyter notebook.\\nThis time we're i...\",\"Video: 59166847\\u003cbr\\u003eText: Well, they say that time flies when you're having fun, and it certainly feels like time is flying.\\nU...\",\"Video: 59170223\\u003cbr\\u003eText: Well.\\nFantastic.\\nIt's coming up to the end of the week, and that means it's coming up to a challenge...\",\"Video: 59170037\\u003cbr\\u003eText: So how does it feel to be 30% of the way down the journey to being a proficient LLM engineer?\\nTake a...\",\"Video: 59295609\\u003cbr\\u003eText: You must be feeling absolutely exhausted at this point.\\nAnd if you are, that is okay.\\nYou have done ...\",\"Video: 60619281\\u003cbr\\u003eText: Well, I'm delighted to welcome you to day three of our eight week journey together.\\nAnd today we're ...\",\"Video: 59472429\\u003cbr\\u003eText: And continuing on our strategy to solve commercial problems with LMS, we get to step four, which is\\n...\",\"Video: 59167009\\u003cbr\\u003eText: Welcome back.\\nIt's time to make our full agent framework.\\nI'm super excited about this.\\nIt's pulling...\",\"Video: 59166481\\u003cbr\\u003eText: And here, once more we find ourselves in our favorite place, the Jupyter Lab.\\nReady to go with weeks...\",\"Video: 59670933\\u003cbr\\u003eText: I realized my enthusiasm for this project is a bit insane, but I have to tell you that I am very sat...\",\"Video: 59670073\\u003cbr\\u003eText: Okay, it's time to complete the Rag workflow in our Jupyter Lab on day 2.3.\\nWe've got this function ...\",\"Video: 59673595\\u003cbr\\u003eText: That concludes a mammoth project.\\nThree weeks in the making.\\nIn the course of those three weeks, sta...\",\"Video: 59297603\\u003cbr\\u003eText: And I'm delighted to welcome you back to LM engineering on the day that we turn to vectors.\\nFinally,...\",\"Video: 60614541\\u003cbr\\u003eText: I am delighted to welcome you to the first day of our eight weeks together as you join me on this ad...\",\"Video: 59667357\\u003cbr\\u003eText: Let's now see our results side by side.\\nWe started our journey with a constant model that was at $1....\",\"Video: 59667841\\u003cbr\\u003eText: Now, look, I know that I went through that very fast, but maybe, uh, you're still, uh, blinking\\nat t...\",\"Video: 59472007\\u003cbr\\u003eText: So I hope you enjoyed our first bash at Scrubbing Data, and that you are now looking through the cod...\",\"Video: 59507435\\u003cbr\\u003eText: So I'm now going to talk about five important 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faster through the other models.\\nWe'll start with Google's Gemini.\\nI have the...\",\"Video: 59472873\\u003cbr\\u003eText: So it's quite an adventure that we had at the frontier of what's capable with Llms today, solving a\\n...\",\"Video: 60619429\\u003cbr\\u003eText: Let me talk about some other phenomena that have happened over the last few years.\\nOne of them has b...\",\"Video: 59295601\\u003cbr\\u003eText: So it's time to continue our journey into the world of open source and understand which models we sh...\",\"Video: 59170025\\u003cbr\\u003eText: And a massive welcome back one more time to LM engineering.\\nWe are in week three, day two and we are...\",\"Video: 59166443\\u003cbr\\u003eText: And welcome back everybody.\\nWelcome to week two day three.\\nIt's a continuation of our enjoyment of r...\",\"Video: 60620025\\u003cbr\\u003eText: And welcome back to Jupyter Lab, one of my very favorite places to be.\\nWhen Jupyter Lab sprung up on...\",\"Video: 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Chroma Vector Store Visualization\"},\"scene\":{\"xaxis\":{\"title\":{\"text\":\"x\"}},\"yaxis\":{\"title\":{\"text\":\"y\"}},\"zaxis\":{\"title\":{\"text\":\"z\"}}},\"width\":900,\"height\":700}, {\"responsive\": true} ).then(function(){\n", |
|
" \n", |
|
"var gd = document.getElementById('6e775494-6bdd-4cf4-ab4f-18f0e647109b');\n", |
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"var x = new MutationObserver(function (mutations, observer) {{\n", |
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" var display = window.getComputedStyle(gd).display;\n", |
|
" if (!display || display === 'none') {{\n", |
|
" console.log([gd, 'removed!']);\n", |
|
" Plotly.purge(gd);\n", |
|
" observer.disconnect();\n", |
|
" }}\n", |
|
"}});\n", |
|
"\n", |
|
"// Listen for the removal of the full notebook cells\n", |
|
"var notebookContainer = gd.closest('#notebook-container');\n", |
|
"if (notebookContainer) {{\n", |
|
" x.observe(notebookContainer, {childList: true});\n", |
|
"}}\n", |
|
"\n", |
|
"// Listen for the clearing of the current output cell\n", |
|
"var outputEl = gd.closest('.output');\n", |
|
"if (outputEl) {{\n", |
|
" x.observe(outputEl, {childList: true});\n", |
|
"}}\n", |
|
"\n", |
|
" }) }; }); </script> </div>" |
|
] |
|
}, |
|
"metadata": {}, |
|
"output_type": "display_data" |
|
} |
|
], |
|
"source": [ |
|
"# Let's try 3D!\n", |
|
"\n", |
|
"tsne = TSNE(n_components=3, random_state=42)\n", |
|
"reduced_vectors = tsne.fit_transform(vectors)\n", |
|
"\n", |
|
"# Create the 3D scatter plot\n", |
|
"fig = go.Figure(data=[go.Scatter3d(\n", |
|
" x=reduced_vectors[:, 0],\n", |
|
" y=reduced_vectors[:, 1],\n", |
|
" z=reduced_vectors[:, 2],\n", |
|
" mode='markers',\n", |
|
" marker=dict(size=5, color=colors, opacity=0.8),\n", |
|
" text=[f\"Video: {t}<br>Text: {d[:100]}...\" for t, d in zip(video_numbers, documents)],\n", |
|
" hoverinfo='text'\n", |
|
")])\n", |
|
"\n", |
|
"fig.update_layout(\n", |
|
" title='3D Chroma Vector Store Visualization',\n", |
|
" scene=dict(xaxis_title='x', yaxis_title='y', zaxis_title='z'),\n", |
|
" width=900,\n", |
|
" height=700,\n", |
|
" margin=dict(r=20, b=10, l=10, t=40)\n", |
|
")\n", |
|
"\n", |
|
"fig.show()" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": null, |
|
"id": "9b3ada26-b4b7-42fc-b943-933c14adf89b", |
|
"metadata": {}, |
|
"outputs": [], |
|
"source": [] |
|
} |
|
], |
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"metadata": { |
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"kernelspec": { |
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"display_name": "Python 3 (ipykernel)", |
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"language": "python", |
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"name": "python3" |
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}, |
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"language_info": { |
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"codemirror_mode": { |
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"name": "ipython", |
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"version": 3 |
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}, |
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"file_extension": ".py", |
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"name": "python", |
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"nbconvert_exporter": "python", |
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"pygments_lexer": "ipython3", |
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"version": "3.11.11" |
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} |
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"nbformat": 4, |
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"nbformat_minor": 5 |
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}
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