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
- [Misc]: TTFT profiling with respect to prompt length
- [Bug]: Gemma 2 9b errors
- [Bug]: Unusual Memory Usage on H100 with Meta llama 8-B 72 GB it should not be around 8x2x1.2 in bfloat16
- [Usage]: Seeing perf regression using chunked_prefill on VLLM 0.5.4
- [Feature]: Enable Prefix caching kernel on Pallas for TPU backend
- [Bug]: vllm server 部署base和lora模型后,请求lora模型失败
- [Bug]: The error is caused by: RuntimeError: out must have shape (total_q, num_heads, head_size_og), leading to the following error: vllm.engine.async_llm_engine.AsyncEngineDeadError: Background loop has errored already.
- [Installation]: container images - too big and need to publish also cpu versions
- [Bug]: Phi-3-small-128k-instruct on 4 T4 GPUs - Memory error: Tried to allocate 1024.00 GiB
- [Build/CI] Empty commit. Testing the present CI state.
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