{"data":{"slug":"wangrongsheng-awesome-llm-resources","name":"awesome-LLM-resources","tagline":"Summary of the world's best LLM resources.","github_url":"https://github.com/WangRongsheng/awesome-LLM-resources","owner":"WangRongsheng","repo":"awesome-LLM-resources","owner_avatar_url":"https://avatars.githubusercontent.com/u/55651568?v=4","primary_language":null,"stars":8845,"forks":950,"topics":["awesome-list","book","course","large-language-models","llama","llm","mistral","openai","qwen","rag","retrieval-augmented-generation","webui"],"archived":false,"github_pushed_at":"2026-08-14T15:54:28+00:00","maintenance_label":"Very active","stars_delta_30d":142,"url":"https://www.graphcanon.com/tools/wangrongsheng-awesome-llm-resources","markdown_url":"https://www.graphcanon.com/tools/wangrongsheng-awesome-llm-resources.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/wangrongsheng-awesome-llm-resources","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=wangrongsheng-awesome-llm-resources","description":"🧑🚀 全世界最好的LLM资料总结（多模态生成、Agent、辅助编程、AI审稿、数据处理、模型训练、模型推理、o1 模型、MCP、小语言模型、视觉语言模型） | Summary of the world's best LLM resources. ","homepage_url":null,"license":"Apache-2.0","open_issues":23,"watchers":84,"ai_summary":"Curates an extensive list of Large Language Model (LLM) related projects and resources including model training, inference, evaluation, and more.","readme_excerpt":"
全世界最好的大语言模型资源汇总 持续更新
\n\n
挖掘那些真正有价值的项目，而不仅仅是噱头
\n\n
\n \n \n \n \n \n\n
\n\n> [!TIP]\n> 如果您对**医疗数据集/大模型/多模态/评估相关资源感兴趣**！请访问我们的 🤗 [Awesome-AI4Med](https://github.com/FreedomIntelligence/Awesome-AI4Med) !\n\n---\n\n#### Contents\n\n- [推荐 Suggestion](#推荐-Suggestion) 🌟\n- [数据 Data](#数据-Data)\n- [微调 Fine-Tuning](#微调-Fine-Tuning) \n- [Agentic RL](#Agentic-RL) 🌟\n- [推理 Inference](#推理-Inference)\n- [评估 Evaluation](#评估-Evaluation)\n- [体验 Usage](#体验-Usage)\n- [知识库 RAG](#知识库-RAG)\n- [智能体 Agents](#智能体-Agents)\n- [研究 Research](#研究-Research) 🔥\n- [代码 Coding](#代码-Coding)\n- [视频 Video](#视频-Video) \n- [图片 Image](#图片-Image) 🔥\n- [搜索 Search](#搜索-Search)\n- [语音 Speech](#语音-Speech) 🔥\n- [世界模型 World Models](#世界模型-World-Models) 🔥\n- [龙虾 OpenClaw](#龙虾-OpenClaw)\n- [统一模型 Unified Model](#统一模型-Unified-Model) 🌟\n- [书籍 Book](#书籍-Book)\n- [课程 Course](#课程-Course)\n- [教程 Tutorial](#教程-Tutorial)\n- [论文 Paper](#论文-Paper)\n- [社区 Community](#社区-Community)\n- [模型上下文协议 MCP](#模型上下文协议-MCP)\n- [技能 Skills](#技能-Skills) \n- [推理 Open o1](#推理-Open-o1)\n- [推理 Open o3](#推理-Open-o3)\n- [小语言模型 Small Language Model](#小语言模型-Small-Language-Model) 🌟\n- [小多模态模型 Small Vision Language Model](#小多模态模型-Small-Vision-Language-Model) 🌟\n- [技巧 Tips](#技巧-tips)\n\n\n\n## 推荐 Suggestion\n\n#### Podcast\n\n- [谷歌AI的14年、Gemini翻身之战，与视觉理解模型：专访DeepMind前核心科学家Andrew Dai｜Neolabs特辑](https://www.youtube.com/watch?v=cqW_VWYbIcU)\n- [140. 对姚顺宇的4小时访谈：请允许我小疯一下！在Anthropic和Gemini训模型、技术预测、英雄主义已过去](https://www.youtube.com/watch?v=Gk_KUg3qED0)\n- [张驰: A Year Inside ByteDance's AI Lab](https://changche.substack.com/p/a-year-inside-bytedances-ai-lab)\n- [Luo Fuli: OpenClaw, Agent Frameworks — The AI Paradigm Has Already Changed Dramatically!](https://www.youtube.com/watch?v=V9eI-t3TApE)\n- [A 7-hour marathon interview with Saining Xie: World Models, AMI Labs, Yann LeCun, Fei-Fei Li, and 42](https://www.youtube.com/watch?v=rIwgZWzUKm8)\n- [翁家翌：OpenAI，GPT，强化学习，Infra，后训练，天授，tuixue，开源，CMU，清华｜WhynotTV Podcast](https://www.bilibili.com/video/BV1darmBcE4A?vd_source=c739db1ebdd361d47af5a0b8497417db)\n- [Lovart 创始人陈冕×罗永浩！且让我大闹一场，然后悄然离去](https://www.bilibili.com/video/BV14eiQBmEbN/?spm_id_from=333.1387.upload.video_card.click)\n- [MiniMax 创始人闫俊杰×罗永浩！大山并非无法翻越](https://www.bilibili.com/video/BV11NmtBzE36/?spm_id_from=333.1387.upload.video_card.click&vd_source=c739db1ebdd361d47af5a0b8497417db)\n- [影视飓风TIM×罗永浩！用影像打开世界的梦想家](https://www.bilibili.com/video/BV1B5xkzPEhx/?spm_id_from=333.1387.upload.video_card.click&vd_source=c739db1ebdd361d47af5a0b8497417db)\n- [129. 全球大模型第一股的上市访谈，和智谱CEO张鹏聊：敢问路在何方？](https://www.youtube.com/watch?v=9zSMTUUEfmU&list=PLwAchVoh-4zNSI5UlKEkKCL5r_jJyrFeO&index=2)\n- [128. Manus决定出售前最后的访谈：啊，这奇幻的2025年漂流啊…](https://www.youtube.com/watch?v=MW-ezf2RhVg&list=PLwAchVoh-4zNSI5UlKEkKCL5r_jJyrFeO&index=3)\n- [122. 朱啸虎现实主义故事的第三次连载：人工智能的盛筵与泡泡](https://www.youtube.com/watch?v=wK0-m3rKgZ0&list=PLwAchVoh-4zNSI5UlKEkKCL5r_jJyrFeO&index=9)\n- [119. Kimi Linear、Minimax M2？和杨松琳考古算法变种史，并预演未来架构改进方案](https://www.youtube.com/watch?v=858HR43pegk&list=PLwAchVoh-4zNSI5UlKEkKCL5r_jJyrFeO&index=12&t=1070s)\n- [118. 对李想的第二次3小时访谈：CEO大模型、MoE、梁文锋、VLA、能量、记忆、对抗人性、亲密关系、人类的智慧](https://www.youtube.com/watch?v=RxXVq7-sJzM&list=PLwAchVoh-4zNSI5UlKEkKCL5r_jJyrFeO&index=13)\n- [115. 对OpenAI姚顺雨3小时访谈：6年Agent研究、人与系统、吞噬的边界、既单极又多元的世界](https://www.youtube.com/watch?v=g","github_created_at":"2024-04-19T03:31:13+00:00","created_at":"2026-07-07T17:34:16.702591+00:00","updated_at":"2026-08-17T06:02:10.670241+00:00","categories":[{"slug":"ai-agents","name":"AI Agents","url":"https://www.graphcanon.com/categories/ai-agents","markdown_url":"https://www.graphcanon.com/categories/ai-agents.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/ai-agents"},{"slug":"developer-tools","name":"Developer Tools","url":"https://www.graphcanon.com/categories/developer-tools","markdown_url":"https://www.graphcanon.com/categories/developer-tools.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/developer-tools"},{"slug":"evaluation-observability","name":"Evaluation & Observability","url":"https://www.graphcanon.com/categories/evaluation-observability","markdown_url":"https://www.graphcanon.com/categories/evaluation-observability.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/evaluation-observability"},{"slug":"inference-serving","name":"Inference & Serving","url":"https://www.graphcanon.com/categories/inference-serving","markdown_url":"https://www.graphcanon.com/categories/inference-serving.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/inference-serving"},{"slug":"llm-frameworks","name":"LLM Frameworks","url":"https://www.graphcanon.com/categories/llm-frameworks","markdown_url":"https://www.graphcanon.com/categories/llm-frameworks.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/llm-frameworks"},{"slug":"model-training","name":"Model Training","url":"https://www.graphcanon.com/categories/model-training","markdown_url":"https://www.graphcanon.com/categories/model-training.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/model-training"}],"tags":[{"slug":"awesome-list","name":"awesome-list"},{"slug":"book","name":"book"},{"slug":"course","name":"course"},{"slug":"large-language-models","name":"large language models"},{"slug":"llama","name":"llama"},{"slug":"llm","name":"llm"},{"slug":"mistral","name":"mistral"},{"slug":"openai","name":"openai"}],"trust":{"provenance":{"is_fork":false,"github_id":788768107,"owner_type":"User","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-17T06:02:09.956Z","maintenance":{"label":"Very active","score":96,"methodology":"github_public_v1","releases_90d":0,"days_since_push":2,"last_release_at":null,"stars_delta_30d":142,"open_issues_delta_30d":-13},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T11:02:50.350Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-08-17T06:02:10.378Z"},"license_spdx":{"value":"Apache-2.0","source":"github.license","observed_at":"2026-08-17T06:02:10.378Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["- It's ideal when you seek an exhaustive and up-to-date compilation covering extensive knowledge points in LLM technologies.","- If you require access to diverse resources including frameworks for model creation, serving, AI agents, data processing, training methods, inference techniques, evaluation methodologies, and more."],"when_not_to_use":["- Avoid using this resource if you specifically need detailed step-by-step guides or hands-on tutorials that focus deeply on a single technology rather than broad coverage.","- It might not be the best choice when you are looking for resources in languages other than English, especially given its extensive English content."],"source":"enrich:decision_facts","observed_at":"2026-07-10T17:17:52.035Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"awesome-LLM-resources offers a curated and comprehensive list of resources related to Large Language Models (LLMs), including materials for specialized areas like RAG (Retrieval-Augmented Generation) and agentic RL, as a"}]}}
\n 
\n 
\n 
\n \n\n