vllm
https://github.com/vllm-project/vllm
Python
A high-throughput and memory-efficient inference and serving engine for LLMs
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- Issues
- [Kernel][Quantization] Custom Floating-Point Runtime Quantization
- [Bug]: stuck at "generating GPU P2P access cache in /home/luban/.cache/vllm/gpu_p2p_access_cache_for_0,1.json"
- [Misc] Add conftest plugin for applying forking decorator
- [Bug]: RuntimeError in gptq_marlin_24_gemm
- [Misc] add non cuda hf benchmark_througput
- [Feature]: DRY Sampling
- [Feature]: Online Inference on local model with OpenAI Python SDK
- [Bug]: memory leak
- [Bug]: Profiling RuntimeError when `with_stack=True`
- [Bug]: Issue when benchmarking the dynamically served LoRA adapter
- Docs
- Python not yet supported