Add code and env info

chapter01/Chapter 1 - Introduction to Language Models.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "EDe7DsPWmEBV"
+   },
+   "source": [
+    "<h1>Chapter 1 - Introduction to Language Models</h1>\n",
+    "<i>Exploring the exciting field of Language AI</i>\n",
+    "\n",
+    "\n",
+    "<a href=\"https://www.amazon.com/Hands-Large-Language-Models-Understanding/dp/1098150961\"><img src=\"https://img.shields.io/badge/Buy%20the%20Book!-grey?logo=amazon\"></a>\n",
+    "<a href=\"https://www.oreilly.com/library/view/hands-on-large-language/9781098150952/\"><img src=\"https://img.shields.io/badge/O'Reilly-white.svg?logo=data:image/svg%2bxml;base64,PHN2ZyB3aWR0aD0iMzQiIGhlaWdodD0iMjciIHZpZXdCb3g9IjAgMCAzNCAyNyIgZmlsbD0ibm9uZSIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KPGNpcmNsZSBjeD0iMTMiIGN5PSIxNCIgcj0iMTEiIHN0cm9rZT0iI0Q0MDEwMSIgc3Ryb2tlLXdpZHRoPSI0Ii8+CjxjaXJjbGUgY3g9IjMwLjUiIGN5PSIzLjUiIHI9IjMuNSIgZmlsbD0iI0Q0MDEwMSIvPgo8L3N2Zz4K\"></a>\n",
+    "<a href=\"https://github.com/HandsOnLLM/Hands-On-Large-Language-Models\"><img src=\"https://img.shields.io/badge/GitHub%20Repository-black?logo=github\"></a>\n",
+    "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1NOo_hNGE8MuXAUa6UXh3eHzt9X_1mYvc?usp=sharing)\n",
+    "\n",
+    "---\n",
+    "\n",
+    "This notebook is for Chapter 1 of the [Hands-On Large Language Models](https://www.amazon.com/Hands-Large-Language-Models-Understanding/dp/1098150961) book by [Jay Alammar](https://www.linkedin.com/in/jalammar) and [Maarten Grootendorst](https://www.linkedin.com/in/mgrootendorst/).\n",
+    "\n",
+    "---\n",
+    "\n",
+    "<a href=\"https://www.amazon.com/Hands-Large-Language-Models-Understanding/dp/1098150961\">\n",
+    "<img src=\"https://raw.githubusercontent.com/HandsOnLLM/Hands-On-Large-Language-Models/main/images/book_cover.png\" width=\"350\"/></a>\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "hXp09JFsFBXi"
+   },
+   "source": [
+    "# Phi-3\n",
+    "\n",
+    "The first step is to load our model onto the GPU for faster inference. Note that we load the model and tokenizer separately (although that isn't always necessary)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "id": "RSNalRXZyTTk"
+   },
+   "outputs": [],
+   "source": [
+    "from transformers import AutoModelForCausalLM, AutoTokenizer\n",
+    "\n",
+    "# Load model and tokenizer\n",
+    "model = AutoModelForCausalLM.from_pretrained(\n",
+    "    \"microsoft/Phi-3-mini-4k-instruct\",\n",
+    "    device_map=\"cuda\",\n",
+    "    torch_dtype=\"auto\",\n",
+    "    trust_remote_code=True,\n",
+    ")\n",
+    "tokenizer = AutoTokenizer.from_pretrained(\"microsoft/Phi-3-mini-4k-instruct\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "qdyYYS0E5fEU"
+   },
+   "source": [
+    "Although we can now use the model and tokenizer directly, it's much easier to wrap it in a `pipeline` object:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "id": "DiUi4Wu1FCyN"
+   },
+   "outputs": [],
+   "source": [
+    "from transformers import pipeline\n",
+    "\n",
+    "# Create a pipeline\n",
+    "generator = pipeline(\n",
+    "    \"text-generation\",\n",
+    "    model=model,\n",
+    "    tokenizer=tokenizer,\n",
+    "    return_full_text=False,\n",
+    "    max_new_tokens=500,\n",
+    "    do_sample=False\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "mD49kysT5mMY"
+   },
+   "source": [
+    "Finally, we create our prompt as a user and give it to the model:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "id": "hkR7LBmiyXmY"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " Why did the chicken join the band? Because it had the drumsticks!\n"
+     ]
+    }
+   ],
+   "source": [
+    "# The prompt (user input / query)\n",
+    "messages = [\n",
+    "    {\"role\": \"user\", \"content\": \"Create a funny joke about chickens.\"}\n",
+    "]\n",
+    "\n",
+    "# Generate output\n",
+    "output = generator(messages)\n",
+    "print(output[0][\"generated_text\"])"
+   ]
+  }
+ ],
+ "metadata": {
+  "accelerator": "GPU",
+  "colab": {
+   "authorship_tag": "ABX9TyPCWg08aO4e8NWQuYCK5ppF",
+   "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": "3.10.14"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}