KAG is a logical form-guided reasoning and retrieval framework based on OpenSPG engine and LLMs. It is used to build logical reasoning and factual Q&A solutions for professional domain knowledge ba…

RAGChecker: A Fine-grained Framework For Diagnosing RAG

Making data higher-quality, juicier, and more digestible for foundation models! 🍎 🍋 🌽 ➡️ ➡️🍸 🍹 🍷为大模型提供更高质量、更丰富、更易”消化“的数据！

A simple, easy-to-hack GraphRAG implementation

Custom Selenium Chromedriver | Zero-Config | Passes ALL bot mitigation systems (like Distil / Imperva/ Datadadome / CloudFlare IUAM)

A general fine-tuning kit geared toward diffusion models.

Empowering RAG with a memory-based data interface for all-purpose applications!

A programming framework for agentic AI 🤖 PyPi: autogen-agentchat Discord: https://aka.ms/autogen-discord Office Hour: https://aka.ms/autogen-officehour

Python SDK, Proxy Server (LLM Gateway) to call 100+ LLM APIs in OpenAI format - [Bedrock, Azure, OpenAI, VertexAI, Cohere, Anthropic, Sagemaker, HuggingFace, Replicate, Groq]

Finetune Llama 3.3, Mistral, Phi, Qwen 2.5 & Gemma LLMs 2-5x faster with 70% less memory

Samples for CUDA Developers which demonstrates features in CUDA Toolkit

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

Automate browser-based workflows with LLMs and Computer Vision

🟣 LLMs interview questions and answers to help you prepare for your next machine learning and data science interview in 2024.

LLM Inference analyzer for different hardware platforms

A curated list of Artificial Intelligence Top Tools

Unified Efficient Fine-Tuning of 100+ LLMs (ACL 2024)

A playbook for systematically maximizing the performance of deep learning models.

SwissArmyTransformer is a flexible and powerful library to develop your own Transformer variants.

SGLang is a fast serving framework for large language models and vision language models.

LLM inference in C/C++

A modular graph-based Retrieval-Augmented Generation (RAG) system

Get up and running with Llama 3.3, Mistral, Gemma 2, and other large language models.

Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding

An efficient, flexible and full-featured toolkit for fine-tuning LLM (InternLM2, Llama3, Phi3, Qwen, Mistral, ...)

🔥🔥 LLaVA++: Extending LLaVA with Phi-3 and LLaMA-3 (LLaVA LLaMA-3, LLaVA Phi-3)