model_tag='deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B',config='',host=None,port=8000,uvicorn_log_level='info',allow_credentials=False,allowed_origins=['*'],allowed_methods=['*'],allowed_headers=['*'],api_key=None,lora_modules=None,prompt_adapters=None,chat_template=None,chat_template_c...
If that is None, we assume the model weights are not quantized and use `dtype` to determine the data type of the weights. revision: The specific model version to use. It can be a branch name, a tag name, or a commit id. tokenizer_revision: The specific tokenizer version to use. It...
# vLLMroot@server:~# curl --location'http://localhost:8000/v1/chat/completions'\--header'Authorization: Bearer 123456'\--header'Content-Type: application/json'\--data'{"model" : "llama3-8b","messages" : [{"role": "system", "content": "You are a helpful assistant."},{"role": ...
description=("The number of odd-numbered requests to this deployment."), tag_keys=("model",), ) self.my_counter.set_default_tags({"model": "123"}) def __call__(self): self.num_requests += 1 if self.num_requests % 2 == 1: self.my_counter.inc() my_deployment = MyDeployment....
AI inference is when an AI model provides an answer based on data. It's the final step in a complex process of machine learning technology. Artificial intelligence resources Featured product Red Hat OpenShift AI An artificial intelligence (AI) platform that provides tools to rapidly develop, trai...
LSE,log-exp-sum可以定义为:\[ \mathbf{LSE}(\mathcal{I}) = \log \sum_{i \in \mathcal{I}} \exp(\mathbf{q} \cdot \mathbf{k}_i) \tag{1} \]其中\mathbf{k}_i是第i个key向量。相应的注意力输出\mathbf{O}(\mathcal{I})则为:\[ \mathbf{O}(\mathcal{I})=\sum_{i \in \...
各种第三方加速包，flashinfer、turbomind等还有就是sglang比较早支持reward model推理，做O1比较需要，v...
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 --max-model-len=4096 --host xx.xx.xx.xx --port 8001 & /...
With nm-vllm, enterprises have a choice - from cloud, datacenter, to edge - on where to run open-source LLMs with complete control over performance, security, and model lifecycle. Challenges It's Hard to Execute LLMs Deploying LLMs are infrastructure intensive. ...
基础镜像地址:https://quay.io/repository/ascend/vllm-ascend?tab=tags&tag=latest 拉取镜像(v0.7.0.3的正式版本尚未发布) docker pull quay.io/ascend/vllm-ascend:v0.7.3-dev 启动镜像 QwQ-32B 需要70G以上显存,2张64G的卡 代码语言:javascript 代码运行次数:0 运行 AI代码解释 docker run -itd --net...