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InteractiveManual.ipynb ADDED
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+ {
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+ "cells": [
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+ {
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+ "cell_type": "markdown",
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+ "metadata": {
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+ "id": "B3S1AZp6Kc0R"
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+ },
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+ "source": [
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+ "# Installing\n",
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+ "\n",
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+ "If running on Google Colab you will need a Colab Pro+ subscription.\n",
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+ "\n",
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+ "Change the runtime type to a high memory or connect your local machine to colab, launch a vm perhaps.\n",
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+ "\n",
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+ "First, you will need to obtain the LLaMA weights. \n",
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+ "\n",
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+ "You can sign up for the official weights here: https://huggingface.co/docs/transformers/main/model_doc/llama\n",
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+ "\n",
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+ "There are alternative models available on huggingface however. This guide will assume you do not have access to the official weights.\n",
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+ "\n",
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+ "If you do have access to the official weights skip to: Clone the delta weights"
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+ ]
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+ },
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+ {
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+ "cell_type": "markdown",
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+ "metadata": {
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+ "id": "8_MM5GNkKc0T"
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+ },
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+ "source": [
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+ "## Clone the LLaMA weights"
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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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+ "metadata": {
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+ "id": "5TioBc7WKc0U"
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+ },
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+ "outputs": [],
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+ "source": [
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+ "# Setup git lfs\n",
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+ "!git lfs install --skip-smudge --force\n",
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+ "!git lfs env\n",
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+ "!git config filter.lfs.process \"git-lfs filter-process --skip\"\n",
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+ "!git config filter.lfs.smudge \"git-lfs smudge --skip -- %f\""
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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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+ "metadata": {
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+ "id": "B5Q-x5yBKc0V"
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+ },
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+ "outputs": [],
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+ "source": [
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+ "# Cloning the 7b parameter model repo\n",
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+ "!git lfs clone https://huggingface.co/decapoda-research/llama-7b-hf"
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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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+ "metadata": {
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+ "id": "d0r8HBUyKc0V"
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+ },
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+ "outputs": [],
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+ "source": [
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+ "# Cloning the 13b parameter model repo\n",
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+ "!git lfs clone https://huggingface.co/decapoda-research/llama-13b-hf"
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+ ]
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+ },
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+ {
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+ "cell_type": "markdown",
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+ "metadata": {
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+ "id": "QeDIT-a4Kc0V"
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+ },
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+ "source": [
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+ "## Applying the Vicuna delta weights"
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+ ]
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+ },
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+ {
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+ "cell_type": "markdown",
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+ "metadata": {
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+ "id": "p7BGGUICKc0W"
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+ },
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+ "source": [
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+ "### Install PyTorch with CUDA support\n",
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+ "\n",
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+ "If you already have this installed in your environment, you can skip this step."
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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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+ "metadata": {
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+ "id": "IfGE0ALrKc0W"
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+ },
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+ "outputs": [],
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+ "source": [
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+ "# First we need to upgrade setuptools, pip and wheel\n",
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+ "!pip install --upgrade setuptools pip wheel"
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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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+ "metadata": {
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+ "id": "RpvAYAD8Kc0W"
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+ },
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+ "outputs": [],
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+ "source": [
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+ "# For CUDA 11.X:\n",
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+ "!pip install nvidia-cuda-runtime-cu11 --index-url https://pypi.ngc.nvidia.com"
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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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+ "metadata": {
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+ "id": "1oEi1ggaKc0X"
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+ },
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+ "outputs": [],
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+ "source": [
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+ "# For CUDA 12.x\n",
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+ "!pip install nvidia-cuda-runtime-cu12 --index-url https://pypi.ngc.nvidia.com"
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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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+ "metadata": {
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+ "id": "fQYYrn4tKc0X"
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+ },
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+ "outputs": [],
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+ "source": [
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+ "# For PyTorch cu117\n",
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+ "!pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu117"
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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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+ "metadata": {
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+ "id": "G7lnb0sYKc0X"
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+ },
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+ "outputs": [],
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+ "source": [
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+ "# For PyTorch cu118\n",
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+ "!pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118"
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+ ]
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+ },
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+ {
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+ "cell_type": "markdown",
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+ "metadata": {
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+ "id": "oBVyjHuWKc0Y"
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+ },
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+ "source": [
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+ "### Running the Fast-Chat apply delta script"
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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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+ "metadata": {
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+ "id": "a4b11Z8lKc0Y"
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+ },
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+ "outputs": [],
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+ "source": [
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+ "# Install FastChat\n",
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+ "!pip install fschat\n",
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+ "\n",
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+ "# Install the latest main branch of huggingface/transformers\n",
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+ "!pip install git+https://github.com/huggingface/transformers"
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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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+ "metadata": {
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+ "id": "3vJTP1m0Kc0Y"
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+ },
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+ "outputs": [],
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+ "source": [
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+ "import json\n",
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+ "\n",
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+ "def convert_llama_names(model_name: str) -> None:\n",
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+ " \"\"\"Convert LlamaForCausalLM to LlamaForCausalLM and LLaMATokenizer to LlamaTokenizer\"\"\"\n",
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+ " with open(f\"{model_name}/config.json\", \"r\", encoding='utf-8') as f:\n",
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+ " data = f.read()\n",
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+ "\n",
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+ " config = json.loads(data)\n",
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+ " config[\"architectures\"] = [\"LlamaForCausalLM\"]\n",
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+ " with open(f\"{model_name}/config.json\", \"w\", encoding='utf-8') as f:\n",
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+ " json.dump(config, f)\n",
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+ "\n",
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+ "\n",
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+ " with open(f\"{model_name}/tokenizer_config.json\", \"r\", encoding='utf-8') as f:\n",
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+ " data = f.read()\n",
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+ "\n",
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+ " config = json.loads(data)\n",
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+ " config[\"tokenizer_class\"] = \"LlamaTokenizer\"\n",
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+ "\n",
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+ " with open(f\"{model_name}/tokenizer_config.json\", \"w\", encoding='utf-8') as f:\n",
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+ " json.dump(config, f)"
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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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+ "metadata": {
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+ "id": "qyboxxkXKc0Y"
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+ },
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+ "outputs": [],
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+ "source": [
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+ "!git lfs clone https://huggingface.co/lmsys/vicuna-7b-delta-v1.1"
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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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+ "metadata": {
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+ "id": "9tlvfvapKc0Z"
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+ },
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+ "outputs": [],
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+ "source": [
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+ "# 7b Model\n",
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+ "convert_llama_names(\"llama-7b-hf\")\n",
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+ "!python -m fastchat.model.apply_delta --base llama-7b-hf --target vicuna-7b --delta ./vicuna-7b-delta-v1.1"
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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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+ "metadata": {
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+ "id": "5VzAdoySKc0Z"
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+ },
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+ "outputs": [],
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+ "source": [
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+ "!git lfs clone https://huggingface.co/lmsys/vicuna-13b-delta-v1.1"
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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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+ "metadata": {
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+ "id": "jRBc7q5RKc0Z"
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+ },
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+ "outputs": [],
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+ "source": [
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+ "# 13b\n",
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+ "convert_llama_names(\"llama-13b-hf\")\n",
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+ "!python -m fastchat.model.apply_delta --base llama-13b-hf --target vicuna-13b --delta ./vicuna-13b-delta-v1.1"
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+ ]
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+ },
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+ {
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+ "cell_type": "markdown",
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+ "metadata": {
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+ "id": "7n8Ug87RKc0Z"
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+ },
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+ "source": [
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+ "# Installing Auto-Vicuna\n",
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+ "\n",
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+ "Note that running this does not work in colab or the notebook, it is for demonstration purposes only."
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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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+ "metadata": {
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+ "id": "gIlfwNlEKc0Z"
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+ },
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+ "outputs": [],
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+ "source": [
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+ "!pip install auto-vicuna"
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+ ]
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+ },
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+ {
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+ "cell_type": "markdown",
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+ "metadata": {
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+ "id": "0Z5NlQOXKc0Z"
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+ },
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+ "source": [
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+ "# Running Auto-Vicuna"
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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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+ "metadata": {
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+ "id": "sBJiQP7MKc0a"
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+ },
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+ "outputs": [],
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+ "source": [
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+ "!auto_vicuna --vicuna_weights vicuna-7b"
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+ ]
296
+ },
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+ {
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+ "cell_type": "markdown",
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+ "metadata": {
300
+ "id": "oqqFeF4zKc0a"
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+ },
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+ "source": [
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+ "You can also create a .env file with \n",
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+ "\n",
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+ "```\n",
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+ "VICUNA_WEIGHTS=vicuna-7b\n",
307
+ "```\n",
308
+ "\n",
309
+ "To avoid passing the weights as an arugment."
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+ ]
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+ },
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+ {
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+ "cell_type": "markdown",
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+ "metadata": {
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+ "id": "jiW98C1KKc0a"
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+ },
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+ "source": []
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+ },
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+ {
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+ "cell_type": "markdown",
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+ "metadata": {
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+ "id": "VE8DhmUrKc0a"
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+ },
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+ "source": [
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+ "## Known Issues\n",
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+ "\n",
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+ "If your model keeps talking about random news articles and suchs the `special_tokens_map.json` and `tokenizer_config.json` need to have to stop tokens populated most likely, you can find them in the repo's root dir."
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+ ]
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+ }
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+ ],
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+ "metadata": {
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+ "kernelspec": {
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+ "display_name": ".venv",
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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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+ "mimetype": "text/x-python",
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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": "3.9.13"
348
+ },
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+ "orig_nbformat": 4,
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+ "colab": {
351
+ "provenance": []
352
+ }
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+ },
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+ "nbformat": 4,
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+ "nbformat_minor": 0
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+ }
added_tokens.json ADDED
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+ "[PAD]": 32000
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+ }
config.json ADDED
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+ {
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+ "_name_or_path": "/workspace/huggyllama_llama-13b",
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+ "architectures": [
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+ "LlamaForCausalLM"
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+ ],
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+ "bos_token_id": 1,
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+ "eos_token_id": 2,
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+ "hidden_act": "silu",
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+ "hidden_size": 5120,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 13824,
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+ "max_position_embeddings": 2048,
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+ "max_sequence_length": 2048,
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+ "model_type": "llama",
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+ "num_attention_heads": 40,
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+ "num_hidden_layers": 40,
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+ "pad_token_id": 0,
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+ "rms_norm_eps": 1e-06,
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+ "tie_word_embeddings": false,
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+ "torch_dtype": "float16",
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+ "transformers_version": "4.28.1",
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+ "use_cache": true,
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+ "vocab_size": 32001
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+ }
generation_config.json ADDED
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+ {
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+ }
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