sgl-project/sglang
SGLang is a high-performance serving framework for large language models and multimodal models.
Efficient Long-Context LLM Serving with Head-Aware KV Reuse and SegPagedAttention
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SGLang is a high-performance serving framework for large language models and multimodal models.
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Simple RL training for reasoning
Miles is an enterprise-facing reinforcement learning framework for LLM and VLM post-training, forked from and co-evolving with slime.
Achieve state of the art inference performance with modern accelerators on Kubernetes
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)