Fast model execution with CUDA/HIP graph Quantizations:GPTQ,AWQ, INT4, INT8, and FP8. Optimized CUDA kernels, including integration with FlashAttention and FlashInfer. Speculative decoding Chunked prefill Performance benchmark: We include a performance benchmark at the end ofour blog post. It ...
Enabling compressed-tensors and fbgemm quantization on rocm in addition to fp8. Fixing scaled_mm required parameters as scale_a and scale_b are going to become non-optional in 2.5rc1 BEFORE SUBMITT...
--gpu-memory-utilization<fraction> The fraction of GPU memory to be used for the model executor, which can range from 0 to 1. For example, a value of 0.5 would imply 50% GPU memory utilization. If unspecified, will use the default value of 0.9. 18.模型执行器使用的显存比例,可以是零到...
tokenizer='/data/sda/models/opt-125m', tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=False, dtype=torch.float16, max_seq_len=2048, download_dir=None, load_format=auto, tensor_parallel_size=1, quantization=None, enforce_eager...
包含KV缓存比例因子的JSON文件路径。当KV缓存数据类型为FP8时,通常应当提供此文件。否则,KV缓存比例因子默认为1.0,可能导致准确性问题。FP8_E5M2(未缩放)仅在CUDA版本大于11.8时支持。在ROCm(AMD GPU)上,相反,支持FP8_E4M3以满足常见的推理标准。 --max-model-len MAX_MODEL_LEN ...
or VLLM_TARGET_DEVICE == "rocm") and torch.version.hip is not None def _is_neuron() -> bool: return VLLM_TARGET_DEVICE == "neuron" def _is_tpu() -> bool: return VLLM_TARGET_DEVICE == "tpu" def _is_cpu() -> bool: ...
使用Nvidia CUDA无需编译,可以直接使用。如果使用AMD ROCm或者Intel的GPU。需要按照官方文档编译之后才能使用。 运行 官方文档参见。GPU — vLLM 使用pip install vllm安装vllm。 mkdir project_path cd project_path python -m venv ./ source bin/activate ...
Fast model execution with CUDA/HIP graph Quantizations: GPTQ, AWQ, INT4, INT8, and FP8. Optimized CUDA kernels, including integration with FlashAttention and FlashInfer. Speculative decoding Chunked prefill Performance benchmark: We include a performance benchmark at the end of our blog post....
如果使用Hugging Face下载模型存在网络问题,可以使用modelscope,使用以下代码下载并加载模型。 1.安装modelscope AI检测代码解析 pipinstallmodelscope 1. 2.下载模型 AI检测代码解析 from modelscopeimportsnapshot_download model_dir=snapshot_download('deepseek-ai/DeepSeek-R1-Distill-Qwen-7B',cache_dir='/root...
vllm [用法]:如何使用Medusa推测性采样推理模型,这是否与#6777相同？