Miles is an enterprise-facing reinforcement learning framework for LLM and VLM post-training, forked from and co-evolving with slime.

FlashInfer: Kernel Library for LLM Serving

A high-throughput and memory-efficient inference and serving engine for LLMs

🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.

verl/HybridFlow: A Flexible and Efficient RL Post-Training Framework

A library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit and 4-bit floating point (FP8 and FP4) precision on Hopper, Ada and Blackwell GPUs, to provide better performance with lower memory utilization in both training and inference.

SGLang is a high-performance serving framework for large language models and multimodal models.

Fast and memory-efficient exact attention