vllm
https://github.com/vllm-project/vllm
Python
A high-throughput and memory-efficient inference and serving engine for LLMs
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Help out
- Issues
- Rocm enable decoder cudagraph
- fix: reject required/named tool_choice for Harmony models without a tool parser
- test(quantization): cover tied lm_head/embed_tokens when lm_head excluded from ModelOpt
- [Model] Add minimal native RWKV7 serving support
- [Bug]: deepseek_v4 parser: reply without </think> routes the whole answer to reasoning_content (content empty), trailing EOS not stripped
- [XPU] upgrade to torch 2.13
- [Bugfix] Fix HYV3 shared_mlp prefix for compressed-tensors ignore matching
- [Bugfix][Parser] Fix streaming tool-call args truncated by schema coercion
- [Bugfix] Make Gemma 4 suppress-token masking CUDA-graph safe
- [Bugfix] Avoid FlashAttention 3 with batch invariance on Hopper
- Docs
- Python not yet supported