LLM 模型排行

Experimental RAG playground for exploring retrieval quality, corpus construction, and filter-chain design. Features configurable ranking and filtering pipelines, visual document grounding, chat interfaces, web search, Open WebUI integration, and rich debugging insights. Ollama and vLLM, running in Dev Containers or natively on Linux and Windows.

A web-based memory usage and performance calculator for Huggingface GGUF models

用于微调LLM的中文指令数据集

A fluent, scalable, and easy-to-use LLM data processing framework.

Tools for the Griptape Framework.

A structured learning repo for retrieval-augmented generation, from foundations to production patterns.

Speak. It types. Typex is an open-source, desktop AI voice input tool.

Uncensor Qwen 3.8 27B with a pre-baked system pack for Ollama, plus GGUF download links.

a simple lightweight large language model pipeline framework.

Dockerized LLM inference server with constrained output (JSON mode), built on top of vLLM and outlines. Faster, cheaper and without rate limits. Compare the quality and latency to your current LLM API provider.

Implementation of Bitune: Bidirectional Instruction-Tuning

A simple, interactive CLI for fine-tuning small language models on Apple Silicon. No YAML configs, no complex flags - just an interactive CLI that guides you through the process.

Turn documents into high-quality instruction datasets with grounding, quality filtering, deduplication, and provenance.

A complete, hands-on roadmap to becoming an AI Engineer, from Python basics to production RAG, Agents, and Fine-Tuning. 10 modules, 20+ notebooks, 15 real projects. Free, open source, built for the community.

Fine tune LLM with HuggingFace

All-in-one UI for merged LLMs in Hugging Face

One Repo To Quickly Build One Docker File for HuggingChat Front and BackEnd

Advanced Coding AI Assistant that uses a Gradio interface to stream coding related responses. ChatRAG supports local and API inference and pulls context from GitHub Repos and local files.

AI assistant for Dota 2 with real-time game analysis via GSI and advice from LLM

🧠 Stop building AI that forgets. Master MCP (Model Context Protocol) with production-ready semantic memory, hybrid RAG, and the WARNERCO Schematica teaching app. FastMCP + LangGraph + Vector/Graph stores. Your AI assistant's long-term memory starts here.