7 changed files with 367 additions and 285 deletions
@ -1,267 +1,277 @@
|
||||
{ |
||||
"nbformat": 4, |
||||
"nbformat_minor": 0, |
||||
"metadata": { |
||||
"colab": { |
||||
"provenance": [], |
||||
"gpuType": "T4" |
||||
}, |
||||
"kernelspec": { |
||||
"name": "python3", |
||||
"display_name": "Python 3" |
||||
}, |
||||
"language_info": { |
||||
"name": "python" |
||||
}, |
||||
"accelerator": "GPU" |
||||
"cells": [ |
||||
{ |
||||
"cell_type": "code", |
||||
"execution_count": null, |
||||
"metadata": { |
||||
"id": "kU2JrcPlhwd9" |
||||
}, |
||||
"outputs": [], |
||||
"source": [ |
||||
"!pip install -q requests torch bitsandbytes transformers sentencepiece accelerate gradio" |
||||
] |
||||
}, |
||||
"cells": [ |
||||
{ |
||||
"cell_type": "code", |
||||
"source": [ |
||||
"!pip install -q requests torch bitsandbytes transformers sentencepiece accelerate gradio" |
||||
], |
||||
"metadata": { |
||||
"id": "kU2JrcPlhwd9" |
||||
}, |
||||
"execution_count": null, |
||||
"outputs": [] |
||||
}, |
||||
{ |
||||
"cell_type": "markdown", |
||||
"source": [ |
||||
"**Imports**" |
||||
], |
||||
"metadata": { |
||||
"id": "lAMIVT4iwNg0" |
||||
} |
||||
}, |
||||
{ |
||||
"cell_type": "code", |
||||
"source": [ |
||||
"import os\n", |
||||
"import requests\n", |
||||
"from google.colab import drive\n", |
||||
"from huggingface_hub import login\n", |
||||
"from google.colab import userdata\n", |
||||
"from transformers import AutoTokenizer, AutoModelForCausalLM, TextStreamer, BitsAndBytesConfig\n", |
||||
"import torch\n", |
||||
"import gradio as gr\n", |
||||
"\n", |
||||
"hf_token = userdata.get('HF_TOKEN')\n", |
||||
"login(hf_token, add_to_git_credential=True)" |
||||
], |
||||
"metadata": { |
||||
"id": "-Apd7-p-hyLk" |
||||
}, |
||||
"execution_count": 2, |
||||
"outputs": [] |
||||
}, |
||||
{ |
||||
"cell_type": "markdown", |
||||
"source": [ |
||||
"**Model**" |
||||
], |
||||
"metadata": { |
||||
"id": "xa0qYqZrwQ66" |
||||
} |
||||
}, |
||||
{ |
||||
"cell_type": "code", |
||||
"source": [ |
||||
"model_name = \"meta-llama/Meta-Llama-3.1-8B-Instruct\"\n", |
||||
"quant_config = BitsAndBytesConfig(\n", |
||||
" load_in_4bit=True,\n", |
||||
" bnb_4bit_use_double_quant=True,\n", |
||||
" bnb_4bit_compute_dtype=torch.bfloat16,\n", |
||||
" bnb_4bit_quant_type=\"nf4\"\n", |
||||
")\n", |
||||
"\n", |
||||
"model = AutoModelForCausalLM.from_pretrained(\n", |
||||
" model_name,\n", |
||||
" device_map=\"auto\",\n", |
||||
" quantization_config=quant_config\n", |
||||
")" |
||||
], |
||||
"metadata": { |
||||
"id": "z5enGmuKjtJu" |
||||
}, |
||||
"execution_count": null, |
||||
"outputs": [] |
||||
}, |
||||
{ |
||||
"cell_type": "markdown", |
||||
"source": [ |
||||
"**Tokenizer**" |
||||
], |
||||
"metadata": { |
||||
"id": "y1hUSmWlwSbp" |
||||
} |
||||
}, |
||||
{ |
||||
"cell_type": "code", |
||||
"source": [ |
||||
"tokenizer = AutoTokenizer.from_pretrained(model_name)\n", |
||||
"tokenizer.pad_token = tokenizer.eos_token" |
||||
], |
||||
"metadata": { |
||||
"id": "WjxNWW6bvdgj" |
||||
}, |
||||
"execution_count": 4, |
||||
"outputs": [] |
||||
}, |
||||
{ |
||||
"cell_type": "markdown", |
||||
"source": [ |
||||
"**Functions**" |
||||
], |
||||
"metadata": { |
||||
"id": "1pg2U-B3wbIK" |
||||
} |
||||
}, |
||||
{ |
||||
"cell_type": "code", |
||||
"source": [ |
||||
"def generate_dataset(topic, number_of_data, inst1, resp1, inst2, resp2, inst3, resp3):\n", |
||||
" # Convert user inputs into multi-shot examples\n", |
||||
" multi_shot_examples = [\n", |
||||
" {\"instruction\": inst1, \"response\": resp1},\n", |
||||
" {\"instruction\": inst2, \"response\": resp2},\n", |
||||
" {\"instruction\": inst3, \"response\": resp3}\n", |
||||
" ]\n", |
||||
"\n", |
||||
" # System prompt\n", |
||||
" system_prompt = f\"\"\"\n", |
||||
" You are a helpful assistant whose main purpose is to generate datasets.\n", |
||||
" Topic: {topic}\n", |
||||
" Return the dataset in JSON format. Use examples with simple, fun, and easy-to-understand instructions for kids.\n", |
||||
" Include the following examples: {multi_shot_examples}\n", |
||||
" Return {number_of_data} examples each time.\n", |
||||
" Do not repeat the provided examples.\n", |
||||
" \"\"\"\n", |
||||
"\n", |
||||
" # Example Messages\n", |
||||
" messages = [\n", |
||||
" {\"role\": \"system\", \"content\": system_prompt},\n", |
||||
" {\"role\": \"user\", \"content\": f\"Please generate my dataset for {topic}\"}\n", |
||||
" ]\n", |
||||
"\n", |
||||
" # Tokenize Input\n", |
||||
" inputs = tokenizer.apply_chat_template(messages, return_tensors=\"pt\").to(\"cuda\")\n", |
||||
" streamer = TextStreamer(tokenizer)\n", |
||||
"\n", |
||||
" # Generate Output\n", |
||||
" outputs = model.generate(inputs, max_new_tokens=2000, streamer=streamer)\n", |
||||
"\n", |
||||
" # Decode and Return\n", |
||||
" return tokenizer.decode(outputs[0], skip_special_tokens=True)\n", |
||||
"\n", |
||||
"\n", |
||||
"def gradio_interface(topic, number_of_data, inst1, resp1, inst2, resp2, inst3, resp3):\n", |
||||
" return generate_dataset(topic, number_of_data, inst1, resp1, inst2, resp2, inst3, resp3)" |
||||
], |
||||
"metadata": { |
||||
"id": "ZvljDKdji8iV" |
||||
}, |
||||
"execution_count": 12, |
||||
"outputs": [] |
||||
}, |
||||
{ |
||||
"cell_type": "markdown", |
||||
"source": [ |
||||
"**Default Values**" |
||||
], |
||||
"metadata": { |
||||
"id": "_WDZ5dvRwmng" |
||||
} |
||||
}, |
||||
{ |
||||
"cell_type": "code", |
||||
"source": [ |
||||
"default_topic = \"Talking to a (5-8) years old and teaching them manners.\"\n", |
||||
"default_number_of_data = 10\n", |
||||
"default_multi_shot_examples = [\n", |
||||
" {\n", |
||||
" \"instruction\": \"Why do I have to say please when I want something?\",\n", |
||||
" \"response\": \"Because it’s like magic! It shows you’re nice, and people want to help you more.\"\n", |
||||
" },\n", |
||||
" {\n", |
||||
" \"instruction\": \"What should I say if someone gives me a toy?\",\n", |
||||
" \"response\": \"You say, 'Thank you!' because it makes them happy you liked it.\"\n", |
||||
" },\n", |
||||
" {\n", |
||||
" \"instruction\": \"why should I listen to my parents?\",\n", |
||||
" \"response\": \"Because parents want the best for you and they love you the most.\"\n", |
||||
" }\n", |
||||
"]" |
||||
], |
||||
"metadata": { |
||||
"id": "JAdfqYXnvEDE" |
||||
}, |
||||
"execution_count": 13, |
||||
"outputs": [] |
||||
}, |
||||
{ |
||||
"cell_type": "markdown", |
||||
"source": [ |
||||
"**Init gradio**" |
||||
], |
||||
"metadata": { |
||||
"id": "JwZtD032wuK8" |
||||
} |
||||
}, |
||||
{ |
||||
"cell_type": "code", |
||||
"source": [ |
||||
"gr_interface = gr.Interface(\n", |
||||
" fn=gradio_interface,\n", |
||||
" inputs=[\n", |
||||
" gr.Textbox(label=\"Topic\", value=default_topic, lines=2),\n", |
||||
" gr.Number(label=\"Number of Examples\", value=default_number_of_data, precision=0),\n", |
||||
" gr.Textbox(label=\"Instruction 1\", value=default_multi_shot_examples[0][\"instruction\"]),\n", |
||||
" gr.Textbox(label=\"Response 1\", value=default_multi_shot_examples[0][\"response\"]),\n", |
||||
" gr.Textbox(label=\"Instruction 2\", value=default_multi_shot_examples[1][\"instruction\"]),\n", |
||||
" gr.Textbox(label=\"Response 2\", value=default_multi_shot_examples[1][\"response\"]),\n", |
||||
" gr.Textbox(label=\"Instruction 3\", value=default_multi_shot_examples[2][\"instruction\"]),\n", |
||||
" gr.Textbox(label=\"Response 3\", value=default_multi_shot_examples[2][\"response\"]),\n", |
||||
" ],\n", |
||||
" outputs=gr.Textbox(label=\"Generated Dataset\")\n", |
||||
")" |
||||
], |
||||
"metadata": { |
||||
"id": "xy2RP5T-vxXg" |
||||
}, |
||||
"execution_count": 14, |
||||
"outputs": [] |
||||
}, |
||||
{ |
||||
"cell_type": "markdown", |
||||
"source": [ |
||||
"**Run the app**" |
||||
], |
||||
"metadata": { |
||||
"id": "HZx-mm9Uw3Ph" |
||||
} |
||||
}, |
||||
{ |
||||
"cell_type": "code", |
||||
"source": [ |
||||
"gr_interface.launch()" |
||||
], |
||||
"metadata": { |
||||
"id": "bfGs5ip8mndg" |
||||
}, |
||||
"execution_count": null, |
||||
"outputs": [] |
||||
}, |
||||
{ |
||||
"cell_type": "code", |
||||
"source": [], |
||||
"metadata": { |
||||
"id": "Cveqx392x7Mm" |
||||
}, |
||||
"execution_count": null, |
||||
"outputs": [] |
||||
} |
||||
] |
||||
} |
||||
{ |
||||
"cell_type": "markdown", |
||||
"metadata": { |
||||
"id": "lAMIVT4iwNg0" |
||||
}, |
||||
"source": [ |
||||
"**Imports**" |
||||
] |
||||
}, |
||||
{ |
||||
"cell_type": "code", |
||||
"execution_count": 2, |
||||
"metadata": { |
||||
"id": "-Apd7-p-hyLk" |
||||
}, |
||||
"outputs": [], |
||||
"source": [ |
||||
"import os\n", |
||||
"import requests\n", |
||||
"from google.colab import drive\n", |
||||
"from huggingface_hub import login\n", |
||||
"from google.colab import userdata\n", |
||||
"from transformers import AutoTokenizer, AutoModelForCausalLM, TextStreamer, BitsAndBytesConfig\n", |
||||
"import torch\n", |
||||
"import gradio as gr\n", |
||||
"\n", |
||||
"hf_token = userdata.get('HF_TOKEN')\n", |
||||
"login(hf_token, add_to_git_credential=True)" |
||||
] |
||||
}, |
||||
{ |
||||
"cell_type": "markdown", |
||||
"metadata": { |
||||
"id": "xa0qYqZrwQ66" |
||||
}, |
||||
"source": [ |
||||
"**Model**" |
||||
] |
||||
}, |
||||
{ |
||||
"cell_type": "code", |
||||
"execution_count": null, |
||||
"metadata": { |
||||
"id": "z5enGmuKjtJu" |
||||
}, |
||||
"outputs": [], |
||||
"source": [ |
||||
"model_name = \"meta-llama/Meta-Llama-3.1-8B-Instruct\"\n", |
||||
"quant_config = BitsAndBytesConfig(\n", |
||||
" load_in_4bit=True,\n", |
||||
" bnb_4bit_use_double_quant=True,\n", |
||||
" bnb_4bit_compute_dtype=torch.bfloat16,\n", |
||||
" bnb_4bit_quant_type=\"nf4\"\n", |
||||
")\n", |
||||
"\n", |
||||
"model = AutoModelForCausalLM.from_pretrained(\n", |
||||
" model_name,\n", |
||||
" device_map=\"auto\",\n", |
||||
" quantization_config=quant_config\n", |
||||
")" |
||||
] |
||||
}, |
||||
{ |
||||
"cell_type": "markdown", |
||||
"metadata": { |
||||
"id": "y1hUSmWlwSbp" |
||||
}, |
||||
"source": [ |
||||
"**Tokenizer**" |
||||
] |
||||
}, |
||||
{ |
||||
"cell_type": "code", |
||||
"execution_count": 4, |
||||
"metadata": { |
||||
"id": "WjxNWW6bvdgj" |
||||
}, |
||||
"outputs": [], |
||||
"source": [ |
||||
"tokenizer = AutoTokenizer.from_pretrained(model_name)\n", |
||||
"tokenizer.pad_token = tokenizer.eos_token" |
||||
] |
||||
}, |
||||
{ |
||||
"cell_type": "markdown", |
||||
"metadata": { |
||||
"id": "1pg2U-B3wbIK" |
||||
}, |
||||
"source": [ |
||||
"**Functions**" |
||||
] |
||||
}, |
||||
{ |
||||
"cell_type": "code", |
||||
"execution_count": 12, |
||||
"metadata": { |
||||
"id": "ZvljDKdji8iV" |
||||
}, |
||||
"outputs": [], |
||||
"source": [ |
||||
"def generate_dataset(topic, number_of_data, inst1, resp1, inst2, resp2, inst3, resp3):\n", |
||||
" # Convert user inputs into multi-shot examples\n", |
||||
" multi_shot_examples = [\n", |
||||
" {\"instruction\": inst1, \"response\": resp1},\n", |
||||
" {\"instruction\": inst2, \"response\": resp2},\n", |
||||
" {\"instruction\": inst3, \"response\": resp3}\n", |
||||
" ]\n", |
||||
"\n", |
||||
" # System prompt\n", |
||||
" system_prompt = f\"\"\"\n", |
||||
" You are a helpful assistant whose main purpose is to generate datasets.\n", |
||||
" Topic: {topic}\n", |
||||
" Return the dataset in JSON format. Use examples with simple, fun, and easy-to-understand instructions for kids.\n", |
||||
" Include the following examples: {multi_shot_examples}\n", |
||||
" Return {number_of_data} examples each time.\n", |
||||
" Do not repeat the provided examples.\n", |
||||
" \"\"\"\n", |
||||
"\n", |
||||
" # Example Messages\n", |
||||
" messages = [\n", |
||||
" {\"role\": \"system\", \"content\": system_prompt},\n", |
||||
" {\"role\": \"user\", \"content\": f\"Please generate my dataset for {topic}\"}\n", |
||||
" ]\n", |
||||
"\n", |
||||
" # Tokenize Input\n", |
||||
" inputs = tokenizer.apply_chat_template(messages, return_tensors=\"pt\").to(\"cuda\")\n", |
||||
" streamer = TextStreamer(tokenizer)\n", |
||||
"\n", |
||||
" # Generate Output\n", |
||||
" outputs = model.generate(inputs, max_new_tokens=2000, streamer=streamer)\n", |
||||
"\n", |
||||
" # Decode and Return\n", |
||||
" return tokenizer.decode(outputs[0], skip_special_tokens=True)\n", |
||||
"\n", |
||||
"\n", |
||||
"def gradio_interface(topic, number_of_data, inst1, resp1, inst2, resp2, inst3, resp3):\n", |
||||
" return generate_dataset(topic, number_of_data, inst1, resp1, inst2, resp2, inst3, resp3)" |
||||
] |
||||
}, |
||||
{ |
||||
"cell_type": "markdown", |
||||
"metadata": { |
||||
"id": "_WDZ5dvRwmng" |
||||
}, |
||||
"source": [ |
||||
"**Default Values**" |
||||
] |
||||
}, |
||||
{ |
||||
"cell_type": "code", |
||||
"execution_count": 13, |
||||
"metadata": { |
||||
"id": "JAdfqYXnvEDE" |
||||
}, |
||||
"outputs": [], |
||||
"source": [ |
||||
"default_topic = \"Talking to a (5-8) years old and teaching them manners.\"\n", |
||||
"default_number_of_data = 10\n", |
||||
"default_multi_shot_examples = [\n", |
||||
" {\n", |
||||
" \"instruction\": \"Why do I have to say please when I want something?\",\n", |
||||
" \"response\": \"Because it’s like magic! It shows you’re nice, and people want to help you more.\"\n", |
||||
" },\n", |
||||
" {\n", |
||||
" \"instruction\": \"What should I say if someone gives me a toy?\",\n", |
||||
" \"response\": \"You say, 'Thank you!' because it makes them happy you liked it.\"\n", |
||||
" },\n", |
||||
" {\n", |
||||
" \"instruction\": \"why should I listen to my parents?\",\n", |
||||
" \"response\": \"Because parents want the best for you and they love you the most.\"\n", |
||||
" }\n", |
||||
"]" |
||||
] |
||||
}, |
||||
{ |
||||
"cell_type": "markdown", |
||||
"metadata": { |
||||
"id": "JwZtD032wuK8" |
||||
}, |
||||
"source": [ |
||||
"**Init gradio**" |
||||
] |
||||
}, |
||||
{ |
||||
"cell_type": "code", |
||||
"execution_count": 14, |
||||
"metadata": { |
||||
"id": "xy2RP5T-vxXg" |
||||
}, |
||||
"outputs": [], |
||||
"source": [ |
||||
"gr_interface = gr.Interface(\n", |
||||
" fn=gradio_interface,\n", |
||||
" inputs=[\n", |
||||
" gr.Textbox(label=\"Topic\", value=default_topic, lines=2),\n", |
||||
" gr.Number(label=\"Number of Examples\", value=default_number_of_data, precision=0),\n", |
||||
" gr.Textbox(label=\"Instruction 1\", value=default_multi_shot_examples[0][\"instruction\"]),\n", |
||||
" gr.Textbox(label=\"Response 1\", value=default_multi_shot_examples[0][\"response\"]),\n", |
||||
" gr.Textbox(label=\"Instruction 2\", value=default_multi_shot_examples[1][\"instruction\"]),\n", |
||||
" gr.Textbox(label=\"Response 2\", value=default_multi_shot_examples[1][\"response\"]),\n", |
||||
" gr.Textbox(label=\"Instruction 3\", value=default_multi_shot_examples[2][\"instruction\"]),\n", |
||||
" gr.Textbox(label=\"Response 3\", value=default_multi_shot_examples[2][\"response\"]),\n", |
||||
" ],\n", |
||||
" outputs=gr.Textbox(label=\"Generated Dataset\")\n", |
||||
")" |
||||
] |
||||
}, |
||||
{ |
||||
"cell_type": "markdown", |
||||
"metadata": { |
||||
"id": "HZx-mm9Uw3Ph" |
||||
}, |
||||
"source": [ |
||||
"**Run the app**" |
||||
] |
||||
}, |
||||
{ |
||||
"cell_type": "code", |
||||
"execution_count": null, |
||||
"metadata": { |
||||
"id": "bfGs5ip8mndg" |
||||
}, |
||||
"outputs": [], |
||||
"source": [ |
||||
"gr_interface.launch()" |
||||
] |
||||
}, |
||||
{ |
||||
"cell_type": "code", |
||||
"execution_count": null, |
||||
"metadata": { |
||||
"id": "Cveqx392x7Mm" |
||||
}, |
||||
"outputs": [], |
||||
"source": [] |
||||
} |
||||
], |
||||
"metadata": { |
||||
"accelerator": "GPU", |
||||
"colab": { |
||||
"gpuType": "T4", |
||||
"provenance": [] |
||||
}, |
||||
"kernelspec": { |
||||
"display_name": "Python 3 (ipykernel)", |
||||
"language": "python", |
||||
"name": "python3" |
||||
}, |
||||
"language_info": { |
||||
"codemirror_mode": { |
||||
"name": "ipython", |
||||
"version": 3 |
||||
}, |
||||
"file_extension": ".py", |
||||
"mimetype": "text/x-python", |
||||
"name": "python", |
||||
"nbconvert_exporter": "python", |
||||
"pygments_lexer": "ipython3", |
||||
"version": "3.11.11" |
||||
} |
||||
}, |
||||
"nbformat": 4, |
||||
"nbformat_minor": 4 |
||||
} |
||||
|
Loading…
Reference in new issue