alan_awesome_llm
LLM resources on model, system, application
https://github.com/tangzhenyu/alan_awesome_llm
Last synced: about 16 hours ago
JSON representation
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RAG
- GraphRAG-Ollama-UI
- AnythingLLM - in-one AI app for any LLM with full RAG and AI Agent capabilites.
- MaxKB
- RAGFlow - source RAG (Retrieval-Augmented Generation) engine based on deep document understanding.
- Dify - source LLM app development platform. Dify's intuitive interface combines AI workflow, RAG pipeline, agent capabilities, model management, observability features and more, letting you quickly go from prototype to production.
- FastGPT - based platform built on the LLM, offers out-of-the-box data processing and model invocation capabilities, allows for workflow orchestration through Flow visualization.
- Langchain-Chatchat
- QAnything
- Quivr - augmented generation.
- Verba
- Dify - source LLM app development platform. Dify's intuitive interface combines AI workflow, RAG pipeline, agent capabilities, model management, observability features and more, letting you quickly go from prototype to production.
- AnythingLLM - in-one AI app for any LLM with full RAG and AI Agent capabilites.
- MaxKB
- RAGFlow - source RAG (Retrieval-Augmented Generation) engine based on deep document understanding.
- FastGPT - based platform built on the LLM, offers out-of-the-box data processing and model invocation capabilities, allows for workflow orchestration through Flow visualization.
- Langchain-Chatchat
- QAnything
- Quivr - augmented generation.
- Verba
- FlashRAG
- GraphRAG - based Retrieval-Augmented Generation (RAG) system.
- nano-GraphRAG - to-hack GraphRAG implementation.
- RAG Techniques - Augmented Generation (RAG) systems. RAG systems combine information retrieval with generative models to provide accurate and contextually rich responses.
- FlashRAG
- GraphRAG - based Retrieval-Augmented Generation (RAG) system.
- nano-GraphRAG - to-hack GraphRAG implementation.
- RAG Techniques - Augmented Generation (RAG) systems. RAG systems combine information retrieval with generative models to provide accurate and contextually rich responses.
- ragas
- ragas
- LightRAG - Agent-Generator pipelines.
- RAG-GPT - GPT, leveraging LLM and RAG technology, learns from user-customized knowledge bases to provide contextually relevant answers for a wide range of queries, ensuring rapid and accurate information retrieval.
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数据 Data
- OmniParser
- MinerU - stop, open-source, high-quality data extraction tool, supports PDF/webpage/e-book extraction.
- PDF-Extract-Kit - Quality PDF Content Extraction.
- Parsera - sites with LLMs.
- AotoLabel
- LabelLLM - Source Data Annotation Platform.
- data-juicer - stop data processing system to make data higher-quality, juicier, and more digestible for LLMs!
- data-juicer - stop data processing system to make data higher-quality, juicier, and more digestible for LLMs!
- OmniParser
- PDF-Extract-Kit - Quality PDF Content Extraction.
- Parsera - sites with LLMs.
- LabelLLM - Source Data Annotation Platform.
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微调 Fine-Tuning
- LLaMA-Factory - Tuning of 100+ LLMs.
- unsloth - 5X faster 80% less memory LLM finetuning.
- TRL
- Firefly
- Xtuner - featured toolkit for fine-tuning large models.
- torchtune - PyTorch Library for LLM Fine-tuning.
- AutoTrain - of-the-art Machine Learning models.
- Ludwig - code framework for building custom LLMs, neural networks, and other AI models.
- mistral-finetune - weight codebase that enables memory-efficient and performant finetuning of Mistral's models.
- aikit - tune, build, and deploy open-source LLMs easily!
- H2O-LLMStudio - a framework and no-code GUI for fine-tuning LLMs.
- LitGPT - of-the-art techniques: flash attention, FSDP, 4-bit, LoRA, and more.
- LLMBox
- PaddleNLP - to-use and powerful NLP and LLM library.
- workbench-llamafactory - to-end model development workflow using Llamafactory.
- OpenRLHF - to-use, Scalable and High-performance RLHF Framework (70B+ PPO Full Tuning & Iterative DPO & LoRA & Mixtral).
- LLaMA-Factory - Tuning of 100+ LLMs.
- unsloth - 5X faster 80% less memory LLM finetuning.
- TRL
- Firefly
- Xtuner - featured toolkit for fine-tuning large models.
- torchtune - PyTorch Library for LLM Fine-tuning.
- AutoTrain - of-the-art Machine Learning models.
- Ludwig - code framework for building custom LLMs, neural networks, and other AI models.
- mistral-finetune - weight codebase that enables memory-efficient and performant finetuning of Mistral's models.
- aikit - tune, build, and deploy open-source LLMs easily!
- H2O-LLMStudio - a framework and no-code GUI for fine-tuning LLMs.
- LitGPT - of-the-art techniques: flash attention, FSDP, 4-bit, LoRA, and more.
- workbench-llamafactory - to-end model development workflow using Llamafactory.
- TinyLLaVA Factory - scale Large Multimodal Models.
- LLM-Foundry
- lmms-finetune - 1.5, qwen-vl, llava-interleave, llava-next-video, phi3-v etc.
- Simplifine
- Transformer Lab - tune, and evaluate large language models on your own computer.
- LLMBox
- PaddleNLP - to-use and powerful NLP and LLM library.
- Simplifine
- TinyLLaVA Factory - scale Large Multimodal Models.
- Transformer Lab - tune, and evaluate large language models on your own computer.
- LLM-Foundry
- lmms-finetune - 1.5, qwen-vl, llava-interleave, llava-next-video, phi3-v etc.
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推理 Inference
- ollama
- Open WebUI - friendly WebUI for LLMs (Formerly Ollama WebUI).
- Text Generation WebUI
- Xinference
- LangChain - aware reasoning applications.
- LlamaIndex
- lobe-chat - source, modern-design LLMs/AI chat framework. Supports Multi AI Providers, Multi-Modals (Vision/TTS) and plugin system.
- TensorRT-LLM - LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and build TensorRT engines that contain state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs.
- vllm - throughput and memory-efficient inference and serving engine for LLMs.
- LlamaChat
- NVIDIA ChatRTX
- LM Studio
- chat-with-mlx
- LLM Pricing
- Open Interpreter
- koboldcpp - file way to run various GGML and GGUF models with KoboldAI's UI.
- LLMFarm
- Flowise
- LMDeploy
- RouteLLM - save LLM costs without compromising quality!
- MInference
- Mem0
- SGLang
- MemGPT - term memory and custom tools.
- ollama
- Open WebUI - friendly WebUI for LLMs (Formerly Ollama WebUI).
- Text Generation WebUI
- Xinference
- LangChain - aware reasoning applications.
- LlamaIndex
- lobe-chat - source, modern-design LLMs/AI chat framework. Supports Multi AI Providers, Multi-Modals (Vision/TTS) and plugin system.
- TensorRT-LLM - LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and build TensorRT engines that contain state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs.
- vllm - throughput and memory-efficient inference and serving engine for LLMs.
- LlamaChat
- NVIDIA ChatRTX
- LM Studio
- chat-with-mlx
- LLM Pricing
- Open Interpreter
- Chat-ollama
- chat-ui
- koboldcpp - file way to run various GGML and GGUF models with KoboldAI's UI.
- LLMFarm
- Jan - LLM).
- LMDeploy
- RouteLLM - save LLM costs without compromising quality!
- MInference
- Mem0
- SGLang
- AirLLM
- Flowise
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评估 Evaluation
- lm-evaluation-harness - shot evaluation of language models.
- opencompass - 4,LLaMa2, Qwen,GLM, Claude, etc) over 100+ datasets.
- llm-comparator - by-side, developed.
- lm-evaluation-harness - shot evaluation of language models.
- opencompass - 4,LLaMa2, Qwen,GLM, Claude, etc) over 100+ datasets.
- llm-comparator - by-side, developed.
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体验 Usage
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书籍 Book
- 《大规模语言模型：从理论到实践》
- 《大语言模型》
- 《动手学大模型Dive into LLMs》
- 《动手做AI Agent》
- 《Build a Large Language Model (From Scratch)》
- 《多模态大模型》
- 《Generative AI Handbook: A Roadmap for Learning Resources》
- 《Understanding Deep Learning》
- 《大规模语言模型：从理论到实践》
- 《大语言模型》
- 《动手学大模型Dive into LLMs》
- 《动手做AI Agent》
- 《Build a Large Language Model (From Scratch)》
- 《多模态大模型》
- 《Generative AI Handbook: A Roadmap for Learning Resources》
- 《Understanding Deep Learning》
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课程 Course
- 斯坦福 CS224N: Natural Language Processing with Deep Learning
- 吴恩达: Generative AI for Everyone
- 吴恩达: LLM series of courses
- ACL 2023 Tutorial: Retrieval-based Language Models and Applications
- llm-course: Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
- 微软: Generative AI for Beginners
- 微软: State of GPT
- HuggingFace NLP Course
- 清华 NLP 刘知远团队大模型公开课
- 斯坦福 CS324: Large Language Models
- 普林斯顿 COS 597G (Fall 2022): Understanding Large Language Models
- 约翰霍普金斯 CS 601.471/671 NLP: Self-supervised Models
- openai-cookbook
- Hands on llms - time financial advisor LLM system.
- 滑铁卢大学 CS 886: Recent Advances on Foundation Models
- Mistral: Getting Started with Mistral
- 斯坦福 CS25: Transformers United V4
- Coursera: Chatgpt 应用提示工程
- mistralai-cookbook
- Introduction to Generative AI 2024 Spring
- build nanoGPT
- LLM101n
- Knowledge Graphs for RAG
- LLMs From Scratch (Datawhale Version)
- OpenRAG
- 通往AGI之路
- Interactive visualization of Transformer
- andysingal/llm-course
- LM-class
- 李宏毅 GenAI课程
- Andrej Karpathy - Neural Networks: Zero to Hero
- llm-course: Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
- 微软: Generative AI for Beginners
- 微软: State of GPT
- HuggingFace NLP Course
- 清华 NLP 刘知远团队大模型公开课
- 斯坦福 CS324: Large Language Models
- 斯坦福 CS224N: Natural Language Processing with Deep Learning
- 吴恩达: Generative AI for Everyone
- 吴恩达: LLM series of courses
- ACL 2023 Tutorial: Retrieval-based Language Models and Applications
- LangGPT
- openai-cookbook
- Hands on llms - time financial advisor LLM system.
- 滑铁卢大学 CS 886: Recent Advances on Foundation Models
- Mistral: Getting Started with Mistral
- 斯坦福 CS25: Transformers United V4
- Coursera: Chatgpt 应用提示工程
- LangGPT
- mistralai-cookbook
- 普林斯顿 COS 597G (Fall 2022): Understanding Large Language Models
- 约翰霍普金斯 CS 601.471/671 NLP: Self-supervised Models
- Introduction to Generative AI 2024 Spring
- build nanoGPT
- LLM101n
- Knowledge Graphs for RAG
- LLMs From Scratch (Datawhale Version)
- OpenRAG
- 通往AGI之路
- Interactive visualization of Transformer
- andysingal/llm-course
- LM-class
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教程 Tutorial
- 动手学大模型应用开发
- AI开发者频道
- B站：五里墩茶社
- B站：木羽Cheney
- B站：漆妮妮
- Prompt Engineering Guide
- B站：TechBeat人工智能社区
- B站：黄益贺
- B站：深度学习自然语言处理
- LLM Visualization
- 知乎: 原石人类
- B站：小黑黑讲AI
- B站：面壁的车辆工程师
- 动手学大模型应用开发
- AI开发者频道
- B站：五里墩茶社
- B站：木羽Cheney
- B站：漆妮妮
- Prompt Engineering Guide
- B站：TechBeat人工智能社区
- B站：黄益贺
- B站：深度学习自然语言处理
- LLM Visualization
- 知乎: 原石人类
- B站：面壁的车辆工程师
- B站：AI老兵文哲
- B站：AI老兵文哲
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论文 Paper
- Qwen Technical Report
- Qwen2 Technical Report
- DeepSeek LLM: Scaling Open-Source Language Models with Longtermism
- DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model
- The Llama 3 Herd of Models
- Qwen2 Technical Report
- DeepSeek LLM: Scaling Open-Source Language Models with Longtermism
- DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model
- Baichuan 2: Open Large-scale Language Models
- DataComp-LM: In search of the next generation of training sets for language models
- Hermes-3-Technical-Report
- OLMo: Accelerating the Science of Language Models
- The Llama 3 Herd of Models
- Qwen Technical Report
- Baichuan 2: Open Large-scale Language Models
- DataComp-LM: In search of the next generation of training sets for language models
- OLMo: Accelerating the Science of Language Models
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软件
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Agents
- CrewAI - playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks.
- Coze
- AgentGPT
- XAgent
- AutoGen - studio.com/)
- MobileAgent
- Lagent - based agents.
- Qwen-Agent
- LinkAI
- Baidu APPBuilder
- agentUniverse - agent framework that allows developers to easily build multi-agent applications. Furthermore, through the community, they can exchange and share practices of patterns across different domains.
- LazyLLM
- AgentScope - empowered multi-agent applications in an easier way.
- MoA - of-the-art results.
- Agently
- OmAgent
- Tribe - agent teams.
- CAMEL - agent framework.
- IoA - source framework for collaborative AI agents, enabling diverse, distributed agents to team up and tackle complex tasks through internet-like connectivity.
- Agent Zero
- AutoGen - studio.com/)
- Coze
- AgentGPT
- XAgent
- MobileAgent
- Lagent - based agents.
- Qwen-Agent
- LinkAI
- Baidu APPBuilder
- agentUniverse - agent framework that allows developers to easily build multi-agent applications. Furthermore, through the community, they can exchange and share practices of patterns across different domains.
- LazyLLM
- AgentScope - empowered multi-agent applications in an easier way.
- MoA - of-the-art results.
- Agently
- OmAgent
- Tribe - agent teams.
- CAMEL - agent framework.
- IoA - source framework for collaborative AI agents, enabling diverse, distributed agents to team up and tackle complex tasks through internet-like connectivity.
- Agent Zero
- Agents - source Framework for Data-centric, Self-evolving Autonomous Language Agents.
- Agents - source Framework for Data-centric, Self-evolving Autonomous Language Agents.
- PraisonAI - code solution for building and managing multi-agent LLM systems, focusing on simplicity, customisation, and efficient human-agent collaboration.
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搜索 Search
- MindSearch - based Multi-agent Framework of Web Search Engine (like Perplexity.ai Pro and SearchGPT).
- nanoPerplexityAI - source implementation of perplexity.ai.
- OpenSearch GPT
- OpenSearch GPT
- MindSearch - based Multi-agent Framework of Web Search Engine (like Perplexity.ai Pro and SearchGPT).
- nanoPerplexityAI - source implementation of perplexity.ai.
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Tips
- What We Learned from a Year of Building with LLMs (Part I)
- What We Learned from a Year of Building with LLMs (Part II)
- What We Learned from a Year of Building with LLMs (Part III): Strategy
- 轻松入门大语言模型（LLM）
- LLMs for Text Classification: A Guide to Supervised Learning
- Unsupervised Text Classification: Categorize Natural Language With LLMs
- Text Classification With LLMs: A Roundup of the Best Methods
- LLM Pricing
- What We Learned from a Year of Building with LLMs (Part III): Strategy
- 轻松入门大语言模型（LLM）
- LLMs for Text Classification: A Guide to Supervised Learning
- Unsupervised Text Classification: Categorize Natural Language With LLMs
- Text Classification With LLMs: A Roundup of the Best Methods
- LLM Pricing
- What We Learned from a Year of Building with LLMs (Part I)
- What We Learned from a Year of Building with LLMs (Part II)
Programming Languages
Categories
Sub Categories
Keywords
llm
96
gpt
46
ai
43
llama
43
chatgpt
35
rag
34
agent
33
llms
30
large-language-models
29
openai
28
llama3
26
chatbot
21
python
20
gpt-4
19
mistral
18
qwen
18
deepseek
17
fine-tuning
16
ollama
15
langchain
15
llama2
15
transformers
14
deep-learning
14
pytorch
14
framework
13
llava
12
gemma
12
lora
11
nlp
11
generative-ai
10
deepseek-r1
10
finetuning
10
machine-learning
10
language-model
10
chatglm
10
llmops
10
agents
9
qlora
9
llm-agent
9
inference
8
macos
8
artificial-intelligence
8
peft
8
gemini
8
llm-training
8
instruction-tuning
8
multimodal
8
javascript
8
transformer
8
gpt-4o
7