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Awesome-LLM: a curated list of Large Language Model
GitHub stars and default-branch commits for Hannibal046/Awesome-LLM.
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Build Agentic workflows, RAG pipelines, with rich AI model and tool support on one collaborative workspace. Deploy on cloud, VPC, or self-hosted, so teams move from prototype to production without rebuilding the stack.
A high-throughput and memory-efficient inference and serving engine for LLMs
Local UI to run and train LLMs and diffusion models. Supports GGUF, MLX, Qwen3.8, DeepSeek-V4, MiniMax-H3, Gemma 4, FLUX and more.
An open platform for training, serving, and evaluating large language models. Release repo for Vicuna and Chatbot Arena.
DSPy: The framework for programming—not prompting—language models
SGLang is a high-performance serving framework for large language models and multimodal models.
Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards.
Evals is a framework for evaluating LLMs and LLM systems, and an open-source registry of benchmarks.
MNN: A blazing-fast, lightweight inference engine battle-tested by Alibaba, powering high-performance on-device LLMs and Edge AI.
TensorRT LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and supports state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorRT LLM also contains components to create Python and C++ runtimes that orchestrate the inference execution in a performant way.
20+ high-performance LLMs with recipes to pretrain, finetune and deploy at scale.
Minimal reproduction of DeepSeek R1-Zero
Access large language models from the command-line
The AI Compute Platform for frontier teams. SkyPilot turns fragmented AI compute into one AI supercomputer, so frontier AI teams build custom intelligence faster.
An Easy-to-use, Scalable and High-performance Agentic RL Framework based on Ray (PPO & DAPO & REINFORCE++ & VLM & TIS & vLLM & Ray & Async RL)
LMDeploy is a toolkit for compressing, deploying, and serving LLMs.
Evidently is an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.
Fast, flexible LLM inference
Efficient Triton Kernels for LLM Training
A PyTorch native platform for training generative AI models
A blazing fast inference solution for text embeddings models
Prompt Engineering | Prompt Versioning | Use GPT or other prompt based models to get structured output. Join our discord for Prompt-Engineering, LLMs and other latest research
Harness LLMs with Multi-Agent Programming
Freeing data processing from scripting madness by providing a set of platform-agnostic customizable pipeline processing blocks.
Open-source tools for prompt testing and experimentation, with support for both LLMs (e.g. OpenAI, LLaMA) and vector databases (e.g. Chroma, Weaviate, LanceDB).
Minimalistic large language model 3D-parallelism training
Lighteval is your all-in-one toolkit for evaluating LLMs across multiple backends
OpenAGI: When LLM Meets Domain Experts
Build production-ready LLM applications and advanced agents using Python, LangChain, and LangGraph. This is the companion repository for the book on generative AI with LangChain.