Comments (1)
Addressed by #90
from vllm.
Related Issues (20)
- [Bug] FP8 MoE performance regression since updating to torch 2.3.0
- [Bug]: For RDNA3 (navi31; gfx1100) VLLM_USE_TRITON_FLASH_ATTN=0 currently must be forced HOT 6
- [Feature]: FP6 HOT 12
- [Bug]: vllm/vllm-openai:v0.4.1 becomes unresponsive on specific requests HOT 3
- [Bug]: Failing to find LoRA adapter for MultiLoRA Inference HOT 1
- --kv_cache_dtype fp8 should not check for nvcc HOT 1
- [Doc]: Documentation disappeared
- [RFC]: Refactor FP8 kv-cache HOT 7
- [Performance]: Profile & optimize the BlockManagerV2
- [Tracking issue] [Help wanted]: Deprecate BlockManagerV1
- Virtual Office Hours: May 15 2pm ET HOT 1
- [Installation]: vLLM does not work on old CPU
- [Bug]: v0.4.1 The output results of the MoE kinds models are incorrect on the V100 HOT 4
- [New Model]: OpenELM-3B HOT 2
- [Bug]: AssertionError in neuron_model_runner.py assert len(block_table) == 1
- [Usage]: Experiencing weird import bugs and errors after installing with pip install -e . HOT 3
- [Bug]: Scheduler fail with assertion on "meta-llama/Meta-Llama-3-70B-Instruct" when calling concurrently HOT 2
- [Usage]: I want to know the correspondence between vllm and torch and cuda
- [Misc]: Server Does Not Follow Scheduler Policy HOT 1
- [RFC]: Automate Speculative Decoding HOT 7
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