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
- [Feature]: google/gemma-2-2b supports 8K context length but vllm does not support it.
- [Performance]: attention speed regression 0.6.0 => 0.6.3
- [Frontend] Support suffix in completions API (fill-in-the-middle)
- [Bug]: Multiple inconsistencies wrt BOS injection and BOS duplication
- [Performance]: VLLM 请求数量过多时太慢
- [Feature]: Support for Diff-Transformer to limit noise in attention calculation @ runtime
- [Usage]: Question Regarding VLLM Rate Limit
- 【Frontend】Add sampler_priority and repetition_penalty_range
- [Usage]: When to use flashinfer as the default backend
- [Model] Update MPT model with GLU and rope and add low precision layer norm
- Docs
- Python not yet supported