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Added notebook example.
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‎README.md‎

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query.generate_readme(repo_config, user_config, readme_config)
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```
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Run the sample script in the `examples/example.py` to see a typical code usage.
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Run the sample script in the `examples/example.py` to see a typical code usage. See example on Google Colab: <a src="https://colab.research.google.com/assets/colab-badge.svg" href="https://colab.research.google.com/github.com/souradipp76/ReadMeReady/blob/main/examples/example.ipynb" target="_blank" rel="noopener noreferrer"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a>
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See detailed API references [here](https://souradipp76.github.io/ReadMeReady/reference/).
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‎examples/example.ipynb‎

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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": "0kA97_xH6hlx"
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},
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"source": [
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"# Readme Ready Example"
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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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"source": [
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"## Install Readme Ready"
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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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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "Q2mrR0s6-hfi",
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"outputId": "e816aa5a-8953-49b8-d5f8-37e3ac9b2206"
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},
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"outputs": [],
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"source": [
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"%pip install -U readme-ready huggingface_hub"
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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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"source": [
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"## Set environment variables"
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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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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "SanQ25iEb5My",
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"outputId": "a0bf97d4-1548-4f2f-aac7-e4e0c37237d5"
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},
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"outputs": [],
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"source": [
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"import os\n",
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"from huggingface_hub import login\n",
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"HF_TOKEN = \"hf_fake_token\" # replace with your Hugging Face token\n",
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"OPENAI_API_KEY = \"fake_openai_api_key\" # replace with your OpenAI API key\n",
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"os.environ[\"OPENAI_API_KEY\"] = OPENAI_API_KEY\n",
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"os.environ[\"HF_TOKEN\"] = HF_TOKEN\n",
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"login(token=HF_TOKEN, add_to_git_credential=False)"
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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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"source": [
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"## Download a sample repository"
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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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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "MnYd5wo3lURX",
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"outputId": "e1536c6f-529e-4d01-c7ce-dadd8d0a6ef7"
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},
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"outputs": [],
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"source": [
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"!git clone https://github.com/eth-siplab/TouchPose.git"
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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": 5,
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"metadata": {
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"id": "4YuGtYkBaUbf"
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},
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"outputs": [],
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"source": [
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"!rm -rf ./TouchPose/.gitignore\n",
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"!rm -rf ./TouchPose/.git\n",
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"!rm -rf ./TouchPose/README.md"
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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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"source": [
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"## Generate README of the sample repository"
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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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"colab": {
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"base_uri": "https://localhost:8080/",
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"height": 350
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},
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"id": "Jc-mYnTpOEwl",
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"outputId": "60eeffc4-680a-44cf-96a4-97a9ce4cf39b"
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},
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"outputs": [],
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"source": [
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"\"\"\"\n",
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"Example\n",
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"\"\"\"\n",
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"from readme_ready.query import query\n",
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"from readme_ready.index import index\n",
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"from readme_ready.types import (\n",
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" AutodocReadmeConfig,\n",
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" AutodocRepoConfig,\n",
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" AutodocUserConfig,\n",
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" LLMModels,\n",
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")\n",
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"\n",
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"# Choose model from supported models\n",
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"model = LLMModels.LLAMA2_7B_CHAT_GPTQ\n",
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"\n",
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"# Initialize the repository configuration. `root` refers to the path to the\n",
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"# code repository for which you want to generate a README for. Please download\n",
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"# any code repository from GitHub and use that or if you have your own\n",
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"# repository downloaded (say 'MyRepo') you can use that as well.\n",
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"# Set `name` to the 'MyRepo'.\n",
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"# Set `root` as <path to 'MyRepo'>.\n",
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"# Set `repository_url` to the GitHub URL of 'MyRepo' (if any) else leave blank.\n",
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"# Set `output` as the path to the directory where the README and other metadata\n",
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"# will be generated and saved.\n",
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"# Set other parameters accordingly (or leave as default).\n",
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"\n",
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"repo_config = AutodocRepoConfig (\n",
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" name = \"TouchPose\", # Set repository name\n",
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" root = \"./TouchPose\", # Set path to root directory of the repository\n",
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" repository_url = \"https://github.com/eth-siplab/TouchPose\", # Set url\n",
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" output = \"./output/TouchPose\", # Set path to output directory to save\n",
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" llms = [model],\n",
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" peft_model_path = None, # Set path to PEFT model\n",
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" ignore = [\n",
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" \".*\",\n",
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" \"*package-lock.json\",\n",
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" \"*package.json\",\n",
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" \"node_modules\",\n",
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" \"*dist*\",\n",
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" \"*build*\",\n",
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" \"*test*\",\n",
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" \"*.svg\",\n",
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" \"*.md\",\n",
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" \"*.mdx\",\n",
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" \"*.toml\"\n",
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" ],\n",
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" file_prompt = \"\",\n",
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" folder_prompt = \"\",\n",
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" chat_prompt = \"\",\n",
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" content_type = \"docs\",\n",
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" target_audience = \"smart developer\",\n",
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" link_hosted = True,\n",
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" priority = None,\n",
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" max_concurrent_calls = 50,\n",
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" add_questions = False,\n",
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" device = \"auto\", # Select device \"cpu\" or \"auto\"\n",
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")\n",
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"\n",
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"user_config = AutodocUserConfig(\n",
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" llms = [model]\n",
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")\n",
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"\n",
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"readme_config = AutodocReadmeConfig(\n",
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" # Set comma separated list of README headings\n",
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" headings = \"Description\"\n",
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")\n",
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"\n",
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"index.index(repo_config)\n",
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"query.generate_readme(repo_config, user_config, readme_config)"
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]
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}
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],
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"metadata": {
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"accelerator": "GPU",
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"colab": {
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"collapsed_sections": [
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"7B3jLeQxcaPe"
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],
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"gpuType": "T4",
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"provenance": []
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},
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"kernelspec": {
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"display_name": "gym",
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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": "3.11.9"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 0
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}

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