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
- [Test] Add a randomized test for OpenAI API
- [New Model]: LoRA for Deepseek-coder-7b-instruct is not supported due to vocab size limit
- [Bug]: ValueError: Asking to pad but the tokenizer does not have a padding token. Please select a token to use as `pad_token` `(tokenizer.pad_token = tokenizer.eos_token e.g.)` or add a new pad token via `tokenizer.add_special_tokens({'pad_token': '[PAD]'})`
- [Bug]: Under the beam search setting, the output is abnormal
- [Usage]: Using a base model with a LoRA on top with AsyncLLMEngine for token streaming
- [Bug]: Mistral generation degrades at long lengths
- [New Model]: Please support CogVLM
- [Feature]: FastServe - Fast Distributed Inference Serving for Large Language Models
- [Bug]: Inference outputs are different by prompt length
- [Feature]: Dynamic Memory Compression: Retrofitting LLMs for Accelerated Inference
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- Python not yet supported