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
- [Benchmark] Add block_size option to benchmark_throughput.py
- [Bug]: Met a error when deploying an AWQ model on H20.
- [Feature]: Expert parallel for mixture-of-experts models
- [Feature]: performance optimization by nanoflow
- [Feature]: Add support for `GPTNeoXForSequenceClassification`
- [New Model]: VisionEncoderDecoderModel
- [Misc] add iteration_tokens metric
- [Performance]: The impact of CPU on vLLM performance is significant.
- [Bug]: When use `guided choice` feature, vllm.engine.async_llm_engine.AsyncEngineDeadError
- [Bug]: ValueError: Queue <multiprocessing.queues.Queue object at 0x7f5703d2d0f0> is closed;zipfile.BadZipFile: Bad magic number for file header
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