Comments (1)
Hi @bibutikoley, vLLM doesn't support models in the GGUF format. Please use original precision models or one of the many quantizations we do support, such as GPTQ, AWQ, FP8, etc. Thanks!
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Related Issues (20)
- [Performance]: How use vllm.attention.ops.triton_flash_attention replace flash_attn package HOT 1
- [Bug]: Performance : very slow inference for Mixtral 8x7B Instruct FP8 on H100 with 0.5.0 and 0.5.0.post1 HOT 2
- [Bug]: CUDA illegal memory access error when `enable_prefix_caching=True` HOT 4
- [Bug]: Vllm 0.3.0 got weired output
- [Feature]: LoRA support for Mixtral GPTQ and AWQ HOT 1
- [Feature]: asymmetric tensor parallel
- [Bug]: prefix-caching: inconsistent completions HOT 1
- [Bug]: Distribute Tests PR test fails
- [Bug]: llava-v1.6-mistral-7b-hf prompt template handling error HOT 3
- [Bug]: RuntimeError: CUDA error: no kernel image is available for execution on the device HOT 1
- [Bug]: OOM when setting prompt_logprobs=1 HOT 3
- [RFC]: Refactor Worker and ModelRunner to consolidate control plane communication HOT 10
- [Bug]: Using tensor-parallel-size 4 fails for some models with pyo3_runtime.PanicException: The global thread pool has not been initialized.: ThreadPoolBuildError {"Resource temporarily unavailable" })
- [RFC]: Implement KV cache transferring mechanism in vLLM HOT 2
- [Performance] [Speculative decoding] Speed up autoregressive proposal methods by making sampler CPU serialization optional HOT 2
- [Bug]: Speculative decoding server: `ValueError: could not broadcast input array from shape (513,) into shape (512,)` HOT 11
- [Bug]: Regression in LoRA Adapter loading speed between vllm 0.4.3 and 0.5.0 HOT 3
- [RFC]: Branch based version control, and development version
- [Usage]: how to use marlin kernel for GPTQ model HOT 9
- [Performance]:
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