5.3(1) 4.服务启动与停止 shell 进入部署目录 cd /home/glm5.3 设置节点启动脚本执行权限 chmod +x node.sh 启动 glm5.3 服务 sbatch srun.sh 查看npu运行状态 npusmi info 查看实例和作业运行信息 squeue 示例输出 JOBID PARTITION NAME USER ST TIME NODES NODELIST(REASON) 1 batch glm root R 1:00:00 4 compute[00010003],master0001 停止一项服务 scancel [JOBID],根据上文推理服务的JOBID为1 scancel 1 停止全部服务 scancel me 服务验证与运维 1.推理服务验证 测试方法:向大模型问一个简单的问题,准备如下脚本并保存到check.sh shell !/bin/bash curl H "ContentType: application/json" d '{ "model": "GLM5.3", "messages": [ {"role":"user","content":"你是谁?"} ], "extra": {"openaiproxy":true} }' 成功响应示例: shell sh check.sh {"id":"chatcmpl8895fddee11ca298","object":"chat.completion","created":1788869218,"model":"GLM5.3","choices":[{"index":0,"message":{"role":"assistant","content":"你好!很高兴见到你。我是GLM,Z.ai训练的大语言模型。nn今天我能为你做些什么?无论是回答问题、提供信息,还是进行日常交流,我都很乐意帮助你。","refusal":null,"annotations":null,"audio":null,"functioncall":null,"reasoning":"收到用户的"你好"问候,需要礼貌地回应并引导对话。首先,我应当以热情友好的态度回应,让用户感受到被重视。同时,考虑到这是初次互动,可以主动询问用户需要什么帮助,以展示乐于助人的特质。在语言表达上,要使用自然流畅的中文,避免过于机械化,可以加入一些表情符号增加亲和力。最后,保持开放式的提问方式,鼓励用户进一步表达需求,这样能为后续对话奠定良好基础"},"logprobs":null,"finishreason":"stop","stopreason":154827,"tokenids":null,"routedexperts":null}],"servicetier":null,"systemfingerprint":"vllm0.26.0tp8dp4ep9ba48c36","usage":{"prompttokens":13,"totaltokens":155,"completiontokens":142,"prompttokensdetails":null,"completiontokensdetails":{"reasoningtokens":100,"audiotokens":null,"acceptedpredictiontokens":null,"rejectedpredictiontokens":null}},"promptlogprobs":null,"prompttokenids":null,"prompttext":null,"kvtransferparams":null,"ectransferparams":null,"metrics":null}
来自: