[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-9595":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":10,"language":11,"languages":10,"totalLinesOfCode":10,"stars":12,"forks":13,"watchers":14,"openIssues":15,"contributorsCount":16,"subscribersCount":16,"size":16,"stars1d":17,"stars7d":18,"stars30d":19,"stars90d":16,"forks30d":16,"starsTrendScore":18,"compositeScore":20,"rankGlobal":10,"rankLanguage":10,"license":21,"archived":22,"fork":22,"defaultBranch":23,"hasWiki":22,"hasPages":22,"topics":24,"createdAt":10,"pushedAt":10,"updatedAt":35,"readmeContent":36,"aiSummary":37,"trendingCount":16,"starSnapshotCount":16,"syncStatus":38,"lastSyncTime":39,"discoverSource":40},9595,"llama-cookbook","meta-llama\u002Fllama-cookbook","meta-llama","Welcome to the Llama Cookbook! This is your go to guide for Building with Llama: Getting started with Inference, Fine-Tuning, RAG. We also show you how to solve end to end problems using Llama model family and using them on various provider services  ","https:\u002F\u002Fwww.llama.com",null,"Jupyter Notebook",18350,2740,192,19,0,3,10,29,45,"MIT License",false,"main",[25,26,27,28,29,30,31,32,33,34],"ai","finetuning","langchain","llama","llama2","llm","machine-learning","python","pytorch","vllm","2026-06-12 02:02:09","\u003Ch1 align=\"center\"> Llama Cookbook \u003C\u002Fh1>\n\u003Cp align=\"center\">\n\t\u003Ca href=\"https:\u002F\u002Fllama.developer.meta.com\u002Fjoin_waitlist?utm_source=llama-cookbook&utm_medium=readme&utm_campaign=main\">\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FLlama_API-Join_Waitlist-brightgreen?logo=meta\" \u002F>\u003C\u002Fa>\n\t\u003Ca href=\"https:\u002F\u002Fllama.developer.meta.com\u002Fdocs?utm_source=llama-cookbook&utm_medium=readme&utm_campaign=main\">\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FLlama_API-Documentation-4BA9FE?logo=meta\" \u002F>\u003C\u002Fa>\n\n\u003C\u002Fp>\n\u003Cp align=\"center\">\n\t\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fmeta-llama\u002Fllama-models\u002Fblob\u002Fmain\u002Fmodels\u002F?utm_source=llama-cookbook&utm_medium=readme&utm_campaign=main\">\u003Cimg alt=\"Llama Model cards\" src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FLlama_OSS-Model_cards-green?logo=meta\" \u002F>\u003C\u002Fa>\n\t\u003Ca href=\"https:\u002F\u002Fwww.llama.com\u002Fdocs\u002Foverview\u002F?utm_source=llama-cookbook&utm_medium=readme&utm_campaign=main\">\u003Cimg alt=\"Llama Documentation\" src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FLlama_OSS-Documentation-4BA9FE?logo=meta\" \u002F>\u003C\u002Fa>\n\t\u003Ca href=\"https:\u002F\u002Fhuggingface.co\u002Fmeta-llama\">\u003Cimg alt=\"Hugging Face meta-llama\" src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FHugging_Face-meta--llama-yellow?logo=huggingface\" \u002F>\u003C\u002Fa>\n\n\u003C\u002Fp>\n\u003Cp align=\"center\">\n\t\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fmeta-llama\u002Fsynthetic-data-kit\">\u003Cimg alt=\"Llama Tools Syntethic Data Kit\" src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FLlama_Tools-synthetic--data--kit-orange?logo=meta\" \u002F>\u003C\u002Fa>\n\t\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fmeta-llama\u002Fllama-prompt-ops\">\u003Cimg alt=\"Llama Tools Syntethic Data Kit\" src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FLlama_Tools-llama--prompt--ops-orange?logo=meta\" \u002F>\u003C\u002Fa>\n\u003C\u002Fp>\n\u003Ch2> Official Guide to building with Llama \u003C\u002Fh2>\n\n\n\nWelcome to the official repository for helping you get started with [inference](https:\u002F\u002Fgithub.com\u002Fmeta-llama\u002Fllama-cookbook\u002Ftree\u002Fmain\u002Fgetting-started\u002Finference\u002F), [fine-tuning](https:\u002F\u002Fgithub.com\u002Fmeta-llama\u002Fllama-cookbook\u002Ftree\u002Fmain\u002Fgetting-started\u002Ffinetuning) and [end-to-end use-cases](https:\u002F\u002Fgithub.com\u002Fmeta-llama\u002Fllama-cookbook\u002Ftree\u002Fmain\u002Fend-to-end-use-cases) of building with the Llama Model family.\n\nThis repository covers the most popular community approaches, use-cases and the latest recipes for Llama Text and Vision models.\n\n## Latest Llama 4 recipes\n\n* [Get started](.\u002Fgetting-started\u002Fbuild_with_llama_api.ipynb) with [Llama API](https:\u002F\u002Fbit.ly\u002Fllama-api-main)\n* Integrate [Llama API](https:\u002F\u002Fbit.ly\u002Fllama-api-main) with [WhatsApp](.\u002Fend-to-end-use-cases\u002Fwhatsapp_llama_4_bot\u002FREADME.md)\n* 5M long context using [Llama 4 Scout](.\u002Fgetting-started\u002Fbuild_with_llama_4.ipynb)\n* Analyze research papers with [Llama 4 Maverick](.\u002Fend-to-end-use-cases\u002Fresearch_paper_analyzer\u002FREADME.md)\n* Create a character mind map from a book using [Llama 4 Maverick](.\u002Fend-to-end-use-cases\u002Fbook-character-mindmap\u002FREADME.md)\n\n## Repository Structure:\n\n- [3P Integrations](https:\u002F\u002Fgithub.com\u002Fmeta-llama\u002Fllama-cookbook\u002Ftree\u002Fmain\u002F3p-integrations): Getting Started Recipes and End to End Use-Cases from various Llama providers\n- [End to End Use Cases](https:\u002F\u002Fgithub.com\u002Fmeta-llama\u002Fllama-cookbook\u002Ftree\u002Fmain\u002Fend-to-end-use-cases): As the name suggests, spanning various domains and applications\n- [Getting Started](https:\u002F\u002Fgithub.com\u002Fmeta-llama\u002Fllama-cookbook\u002Ftree\u002Fmain\u002Fgetting-started\u002F): Reference for inferencing, fine-tuning and RAG examples\n- [src](https:\u002F\u002Fgithub.com\u002Fmeta-llama\u002Fllama-cookbook\u002Ftree\u002Fmain\u002Fsrc\u002F): Contains the src for the original llama-recipes library along with some FAQs for fine-tuning.\n\n> Note: We recently did a refactor of the repo, [archive-main](https:\u002F\u002Fgithub.com\u002Fmeta-llama\u002Fllama-cookbook\u002Ftree\u002Farchive-main) is a snapshot branch from before the refactor\n\n## FAQ:\n\n- **Q:** What happened to llama-recipes?\n  **A:** We recently renamed llama-recipes to llama-cookbook.\n\n- **Q:** I have some questions for Fine-Tuning, is there a section to address these?\n  **A:** Check out the Fine-Tuning FAQ [here](https:\u002F\u002Fgithub.com\u002Fmeta-llama\u002Fllama-cookbook\u002Ftree\u002Fmain\u002Fsrc\u002Fdocs\u002F).\n\n- **Q:** Some links are broken\u002Ffolders are missing:\n  **A:** We recently did a refactor of the repo, [archive-main](https:\u002F\u002Fgithub.com\u002Fmeta-llama\u002Fllama-cookbook\u002Ftree\u002Farchive-main) is a snapshot branch from before the refactor.\n\n- **Q:** Where can we find details about the latest models?\n  **A:** Official [Llama models website](https:\u002F\u002Fwww.llama.com).\n\n## Contributing\n\nPlease read [CONTRIBUTING.md](CONTRIBUTING.md) for details on our code of conduct, and the process for submitting pull requests to us.\n\n## License\n\u003C!-- markdown-link-check-disable -->\nSee the License file for Meta Llama 4 [here](https:\u002F\u002Fgithub.com\u002Fmeta-llama\u002Fllama-models\u002Fblob\u002Fmain\u002Fmodels\u002Fllama4\u002FLICENSE) and Acceptable Use Policy [here](https:\u002F\u002Fgithub.com\u002Fmeta-llama\u002Fllama-models\u002Fblob\u002Fmain\u002Fmodels\u002Fllama4\u002FUSE_POLICY.md)\n\nSee the License file for Meta Llama 3.3 [here](https:\u002F\u002Fgithub.com\u002Fmeta-llama\u002Fllama-models\u002Fblob\u002Fmain\u002Fmodels\u002Fllama3_3\u002FLICENSE) and Acceptable Use Policy [here](https:\u002F\u002Fgithub.com\u002Fmeta-llama\u002Fllama-models\u002Fblob\u002Fmain\u002Fmodels\u002Fllama3_3\u002FUSE_POLICY.md)\n\nSee the License file for Meta Llama 3.2 [here](https:\u002F\u002Fgithub.com\u002Fmeta-llama\u002Fllama-models\u002Fblob\u002Fmain\u002Fmodels\u002Fllama3_2\u002FLICENSE) and Acceptable Use Policy [here](https:\u002F\u002Fgithub.com\u002Fmeta-llama\u002Fllama-models\u002Fblob\u002Fmain\u002Fmodels\u002Fllama3_2\u002FUSE_POLICY.md)\n\nSee the License file for Meta Llama 3.1 [here](https:\u002F\u002Fgithub.com\u002Fmeta-llama\u002Fllama-models\u002Fblob\u002Fmain\u002Fmodels\u002Fllama3_1\u002FLICENSE) and Acceptable Use Policy [here](https:\u002F\u002Fgithub.com\u002Fmeta-llama\u002Fllama-models\u002Fblob\u002Fmain\u002Fmodels\u002Fllama3_1\u002FUSE_POLICY.md)\n\nSee the License file for Meta Llama 3 [here](https:\u002F\u002Fgithub.com\u002Fmeta-llama\u002Fllama-models\u002Fblob\u002Fmain\u002Fmodels\u002Fllama3\u002FLICENSE) and Acceptable Use Policy [here](https:\u002F\u002Fgithub.com\u002Fmeta-llama\u002Fllama-models\u002Fblob\u002Fmain\u002Fmodels\u002Fllama3\u002FUSE_POLICY.md)\n\nSee the License file for Meta Llama 2 [here](https:\u002F\u002Fgithub.com\u002Fmeta-llama\u002Fllama-models\u002Fblob\u002Fmain\u002Fmodels\u002Fllama2\u002FLICENSE) and Acceptable Use Policy [here](https:\u002F\u002Fgithub.com\u002Fmeta-llama\u002Fllama-models\u002Fblob\u002Fmain\u002Fmodels\u002Fllama2\u002FUSE_POLICY.md)\n\u003C!-- markdown-link-check-enable -->\n","Llama Cookbook 是一个面向开发者的指南，旨在帮助用户基于Llama模型家族进行推理、微调及端到端问题解决。项目通过Jupyter Notebook提供了一系列详细的教程和示例代码，涵盖了从基础入门到高级应用的各个方面，包括但不限于使用Llama API与第三方服务（如WhatsApp）集成、处理长文本上下文分析以及研究论文解析等场景。此外，它还支持多种机器学习框架如PyTorch，并提供了丰富的社区资源链接，非常适合希望快速上手或深入探索大型语言模型应用的研究人员和开发者。",2,"2026-06-11 03:23:38","top_topic"]