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
- pthread_create failed: Resource temporarily unavailable
- [Feature]: Multi-Proposers support for speculative decoding.
- [Misc]: Random Output Generation with mistralai/Mixtral-8x22B-v0.1
- [Feature]: Is there any plan to support Cross-Layer Attention (CLA) ?
- [Bugfix][Kernel] Reduce GPU L1 cache pressure for act_order and tensor_parallel on smaller GPUs
- [Bug]: deepseek-coder-v2-lite-instruct; Exception in worker VllmWorkerProcess while processing method initialize_cache: [Errno 2] No such file or directory: '/root/.triton/cache/de758c429c9ff1f18930bbd9c3004506/fused_moe_kernel.json.tmp.pid_1528_587007', Traceback (most recent call last):
- [Bug]: VllmWorkerProcess does not exit correctly when TP > 1
- [Bug]: benchmark_throughput gets TypeError: XFormersMetadata.__init__() got an unexpected keyword argument 'is_prompt' wit CPU
- [Usage]: low GPU usage in qwen1.5 110b int4 inference
- [Feature]: Set tensor_parallel_size to -1, to use all available cuda devices
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- Python not yet supported