具体可以参考链接：https://vllm-ascend.readthedocs.io/en/latest/installation.html 3 启动模型 openai兼容接口 vllm serve /usr1/project/models/QwQ-32B --tensor_parallel_size 2 --served-model-name "QwQ-32B" --max-num-seqs 256 -
ascend-llm 简介 本项目基于昇腾310芯片部署大语言模型,目前已经成功运行meta-llama/Llama-2-7b-hf和TinyLlama/TinyLlama-1.1B-Chat-v1.0。 本实践项目由南京大学计算机科学与技术系杜骋同学主导,由朱光辉老师进行指导,由昇腾CANN生态使能团队提供技术支持,并在昇腾开发者大会2024进行了展示。
from vllm import LLM, SamplingParamsprompts = [ "Hello, my name is", "The president of the United States is", "The capital of France is", "The future of AI is",]sampling_params = SamplingParams(temperature=0.8, top_p=0.95)llm = LLM(model="facebook/opt-125m")output...
尝试使用vllm模型,脚本代码如下: fromvllmimportLLM, SamplingParams prompts = ["Hello, my name is","The president of the United States is","The capital of France is","The future of AI is", ] sampling_params = SamplingParams(temperature=0.8, top_p=0.95) llm = LLM(model="facebook/opt-...
MindIE LLM是MindIE解决方案下的大语言模型推理组件,基于昇腾硬件提供业界通用大模型推理能力,同时提供多并发请求的调度功能,支持Continuous Batching、PageAttention、FlashDecoding等加速特性,使能用户高性能推理需求。 MindIE LLM主要提供大模型推理Python API和大模型调度C++ API。
使用ModelScope需要安装库 pip install modelscope 模型的下载支持以下两种方式 - SDK下载 from modelscope import snapshot_download model_dir = snapshot_download('LLM-Research/Meta-Llama-3-8B-Instruct') - Git下载 #请确保 lfs 已经被正确安装 git lfs install git clone https://www.modelscope.cn/LLM...
line17,in<module>frommindspeed.op_builderimportFusionAttentionV2OpBuilderFile"/home/aicc/ModelLink/MindSpeed/mindspeed/op_builder/__init__.py", line11,in<module>from.gmm_builderimportGMMOpBuilderFile"/home/aicc/ModelLink/MindSpeed/mindspeed/op_builder/gmm_builder.py", line3,in<module>importtorch...
export USE_OPENAI=1 sh AscendCloud-LLM/llm_tools/PD_separate/start_servers.sh \ --model=${model} \ --tensor-parallel-size=2 \ --max-model-len=4096 \ --max-num-seqs=256 \ --max-num-batched-tokens=4096 \ --host=0.0.0.0 \ --port=8089 \ --served-model-name ${served-model-...
Community maintained hardware plugin for vLLM on Ascend inferencetransformermodel-servingmlopsascendllmllmopsllm-servingvllm UpdatedMay 30, 2025 Python an edge-real-time anchor-free object detector with decent performance computer-visiondeep-learningpytorchyoloobject-detectiontensorrtmnnedge-computingonnxascen...
The model to consider. https://huggingface.co/Qwen/Qwen2-VL-2B https://huggingface.co/Qwen/Qwen2-VL-7B The closest model vllm already supports. No response What's your difficulty of supporting the model you want? No response