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
- [Installation]: Installation instructions for ROCm can be mainlined
- [Installation]: Failed building wheel for aiohttp Failed to build aiohttp ERROR: Could not build wheels for aiohttp, which is required to install pyprojec t.toml-based projects
- [Usage]: Which branch should I use to test speculative decoding
- [Feature]: Add ability to sample a specific prompt log probability
- [Feature]: Option For Automatic Function Calling For CohereForAI/c4ai-command-r-plus-08-2024
- [Bug]: vllm v0.6.2/v0.6.3 is easy to generate random output if there are many symbols(not words) in prompt
- [Performance]: inference with qwen2.5 using version vLLM 0.6.3 is felt to be slower
- [Bug]: RuntimeError: Error in model execution (input dumped to /tmp/err_execute_model_input_20241016-170451.pkl): view size is not compatible with input tensor's size and stride (at least one dimension spans across two contiguous subspaces). Use .reshape(...) instead.
- [Installation]: issue with docker setup
- [Bug]: Speculative decoding breaks guided decoding.
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- Python not yet supported