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{ |
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"nbformat": 4, |
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"nbformat_minor": 0, |
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"metadata": { |
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"colab": { |
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"provenance": [], |
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"gpuType": "T4" |
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}, |
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"kernelspec": { |
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"name": "python3", |
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"display_name": "Python 3" |
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}, |
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"language_info": { |
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"name": "python" |
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}, |
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"accelerator": "GPU" |
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}, |
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"cells": [ |
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{ |
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"cell_type": "code", |
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"source": [ |
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"!pip install -q requests torch bitsandbytes transformers sentencepiece accelerate gradio" |
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], |
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"metadata": { |
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"id": "kU2JrcPlhwd9" |
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}, |
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"execution_count": null, |
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"outputs": [] |
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}, |
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{ |
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"cell_type": "markdown", |
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"source": [ |
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"**Imports**" |
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], |
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"metadata": { |
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"id": "lAMIVT4iwNg0" |
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} |
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}, |
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{ |
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"cell_type": "code", |
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"source": [ |
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"import os\n", |
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"import requests\n", |
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"from google.colab import drive\n", |
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"from huggingface_hub import login\n", |
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"from google.colab import userdata\n", |
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"from transformers import AutoTokenizer, AutoModelForCausalLM, TextStreamer, BitsAndBytesConfig\n", |
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"import torch\n", |
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"import gradio as gr\n", |
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"\n", |
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"hf_token = userdata.get('HF_TOKEN')\n", |
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"login(hf_token, add_to_git_credential=True)" |
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], |
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"metadata": { |
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"id": "-Apd7-p-hyLk" |
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}, |
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"execution_count": 2, |
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"outputs": [] |
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}, |
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{ |
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"cell_type": "markdown", |
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"source": [ |
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"**Model**" |
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], |
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"metadata": { |
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"id": "xa0qYqZrwQ66" |
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} |
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}, |
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{ |
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"cell_type": "code", |
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"source": [ |
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"model_name = \"meta-llama/Meta-Llama-3.1-8B-Instruct\"\n", |
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"quant_config = BitsAndBytesConfig(\n", |
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" load_in_4bit=True,\n", |
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" bnb_4bit_use_double_quant=True,\n", |
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" bnb_4bit_compute_dtype=torch.bfloat16,\n", |
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" bnb_4bit_quant_type=\"nf4\"\n", |
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")\n", |
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"\n", |
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"model = AutoModelForCausalLM.from_pretrained(\n", |
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" model_name,\n", |
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" device_map=\"auto\",\n", |
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" quantization_config=quant_config\n", |
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")" |
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], |
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"metadata": { |
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"id": "z5enGmuKjtJu" |
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}, |
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"execution_count": null, |
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"outputs": [] |
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}, |
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{ |
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"cell_type": "markdown", |
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"source": [ |
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"**Tokenizer**" |
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], |
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"metadata": { |
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"id": "y1hUSmWlwSbp" |
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} |
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}, |
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{ |
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"cell_type": "code", |
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"source": [ |
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"tokenizer = AutoTokenizer.from_pretrained(model_name)\n", |
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"tokenizer.pad_token = tokenizer.eos_token" |
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], |
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"metadata": { |
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"id": "WjxNWW6bvdgj" |
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}, |
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"execution_count": 4, |
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"outputs": [] |
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}, |
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{ |
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"cell_type": "markdown", |
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"source": [ |
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"**Functions**" |
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], |
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"metadata": { |
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"id": "1pg2U-B3wbIK" |
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} |
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}, |
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{ |
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"cell_type": "code", |
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"source": [ |
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"def generate_dataset(topic, number_of_data, inst1, resp1, inst2, resp2, inst3, resp3):\n", |
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" # Convert user inputs into multi-shot examples\n", |
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" multi_shot_examples = [\n", |
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" {\"instruction\": inst1, \"response\": resp1},\n", |
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" {\"instruction\": inst2, \"response\": resp2},\n", |
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" {\"instruction\": inst3, \"response\": resp3}\n", |
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" ]\n", |
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"\n", |
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" # System prompt\n", |
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" system_prompt = f\"\"\"\n", |
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" You are a helpful assistant whose main purpose is to generate datasets.\n", |
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" Topic: {topic}\n", |
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" Return the dataset in JSON format. Use examples with simple, fun, and easy-to-understand instructions for kids.\n", |
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" Include the following examples: {multi_shot_examples}\n", |
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" Return {number_of_data} examples each time.\n", |
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" Do not repeat the provided examples.\n", |
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" \"\"\"\n", |
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"\n", |
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" # Example Messages\n", |
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" messages = [\n", |
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" {\"role\": \"system\", \"content\": system_prompt},\n", |
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" {\"role\": \"user\", \"content\": f\"Please generate my dataset for {topic}\"}\n", |
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" ]\n", |
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"\n", |
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" # Tokenize Input\n", |
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" inputs = tokenizer.apply_chat_template(messages, return_tensors=\"pt\").to(\"cuda\")\n", |
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" streamer = TextStreamer(tokenizer)\n", |
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"\n", |
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" # Generate Output\n", |
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" outputs = model.generate(inputs, max_new_tokens=2000, streamer=streamer)\n", |
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"\n", |
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" # Decode and Return\n", |
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" return tokenizer.decode(outputs[0], skip_special_tokens=True)\n", |
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"\n", |
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"\n", |
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"def gradio_interface(topic, number_of_data, inst1, resp1, inst2, resp2, inst3, resp3):\n", |
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" return generate_dataset(topic, number_of_data, inst1, resp1, inst2, resp2, inst3, resp3)" |
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], |
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"metadata": { |
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"id": "ZvljDKdji8iV" |
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}, |
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"execution_count": 12, |
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"outputs": [] |
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}, |
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{ |
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"cell_type": "markdown", |
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"source": [ |
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"**Default Values**" |
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], |
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"metadata": { |
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"id": "_WDZ5dvRwmng" |
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} |
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}, |
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{ |
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"cell_type": "code", |
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"source": [ |
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"default_topic = \"Talking to a (5-8) years old and teaching them manners.\"\n", |
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"default_number_of_data = 10\n", |
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"default_multi_shot_examples = [\n", |
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" {\n", |
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" \"instruction\": \"Why do I have to say please when I want something?\",\n", |
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" \"response\": \"Because it’s like magic! It shows you’re nice, and people want to help you more.\"\n", |
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" },\n", |
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" {\n", |
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" \"instruction\": \"What should I say if someone gives me a toy?\",\n", |
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" \"response\": \"You say, 'Thank you!' because it makes them happy you liked it.\"\n", |
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" },\n", |
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" {\n", |
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" \"instruction\": \"why should I listen to my parents?\",\n", |
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" \"response\": \"Because parents want the best for you and they love you the most.\"\n", |
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" }\n", |
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"]" |
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], |
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"metadata": { |
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"id": "JAdfqYXnvEDE" |
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}, |
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"execution_count": 13, |
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"outputs": [] |
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}, |
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{ |
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"cell_type": "markdown", |
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"source": [ |
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"**Init gradio**" |
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], |
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"metadata": { |
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"id": "JwZtD032wuK8" |
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} |
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}, |
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{ |
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"cell_type": "code", |
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"source": [ |
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"gr_interface = gr.Interface(\n", |
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" fn=gradio_interface,\n", |
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" inputs=[\n", |
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" gr.Textbox(label=\"Topic\", value=default_topic, lines=2),\n", |
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" gr.Number(label=\"Number of Examples\", value=default_number_of_data, precision=0),\n", |
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" gr.Textbox(label=\"Instruction 1\", value=default_multi_shot_examples[0][\"instruction\"]),\n", |
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" gr.Textbox(label=\"Response 1\", value=default_multi_shot_examples[0][\"response\"]),\n", |
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" gr.Textbox(label=\"Instruction 2\", value=default_multi_shot_examples[1][\"instruction\"]),\n", |
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" gr.Textbox(label=\"Response 2\", value=default_multi_shot_examples[1][\"response\"]),\n", |
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" gr.Textbox(label=\"Instruction 3\", value=default_multi_shot_examples[2][\"instruction\"]),\n", |
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" gr.Textbox(label=\"Response 3\", value=default_multi_shot_examples[2][\"response\"]),\n", |
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" ],\n", |
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" outputs=gr.Textbox(label=\"Generated Dataset\")\n", |
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")" |
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], |
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"metadata": { |
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"id": "xy2RP5T-vxXg" |
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}, |
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"execution_count": 14, |
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"outputs": [] |
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}, |
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{ |
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"cell_type": "markdown", |
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"source": [ |
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"**Run the app**" |
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], |
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"metadata": { |
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"id": "HZx-mm9Uw3Ph" |
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} |
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}, |
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{ |
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"cell_type": "code", |
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"source": [ |
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"gr_interface.launch()" |
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], |
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"metadata": { |
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"id": "bfGs5ip8mndg" |
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}, |
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"execution_count": null, |
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"outputs": [] |
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}, |
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{ |
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"cell_type": "code", |
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"source": [], |
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"metadata": { |
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"id": "Cveqx392x7Mm" |
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}, |
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"execution_count": null, |
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"outputs": [] |
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} |
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] |
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} |
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