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
- [Bug]: Prefix Caching fails with fp8 quantized KV Cache
- [Bug]: Error When Using quantized Jais on Specific Layers with vLLM (GPTQ is used for quantization)
- [Bug]: Getting subprocess.CalledProcessError: Command '['/usr/bin/gcc',] error message.
- [Bug]: initialization hang if define an environment variable HOST_IP
- [Installation]: How to install the latest version of vLLM with CUDA 11.7 and PyTorch 2.0.1 ?
- [FacebookAI/roberta-large]: vllm support for FacebookAI/roberta-large
- [Feature]: Support HuggingFaceM4/idefics2-8b as vision model
- [Bug]: vllm how to load Yarn-Mistral-7B-128k(24G 4090, maybe max-model-len*black-size limits max-seq-len)
- [Usage]: RuntimeError: CUDA error: no kernel image is available for execution on the device CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect. For debugging consider passing CUDA_LAUNCH_BLOCKING=1. Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.
- [Feature]: beam search mode to allow for more options in sampling process
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