Merge pull request #47 from innovoe/patch-1
Dataset Generator with Gradio
This commit is contained in:
Ed Donner
GitHub
267
week3/community-contributions/dataset_generator.ipynb
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267
week3/community-contributions/dataset_generator.ipynb
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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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