Comments (9)
如果您是单卡显存不够,您可以通过环境变量,限制最大内存消耗:https://github.com/Jittor/JittorLLMs#%E9%85%8D%E7%BD%AE%E8%A6%81%E6%B1%82%E4%BD%8E
如果您是想用不同的卡,设置环境变量device_id=x
, x是您指定的显卡id
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我们是想对接公司内部客服系统,所以想试试多显卡接线能力,设置device_id=0,1,2,3是不是就支持4显卡了?
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device_id=0 api.py chatglm
device_id=1 api.py chatglm
device_id=2 api.py chatglm
device_id=3 api.py chatglm
您可能需要启动4个进程,然后每个进程使用不同的端口
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修改端口代码在这里:https://github.com/Jittor/JittorLLMs/blob/main/api.py#L48
您可能需要改一下代码
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能不能在一个api自动开多线程并加入自动调用空闲gpu的能力
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谢谢
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您可以自行开发这个功能,理论上几行代码就可以了,在api里面,启动一个multiprocess pool即可
from jittorllms.
device_id=0 api.py chatglm device_id=1 api.py chatglm device_id=2 api.py chatglm device_id=3 api.py chatglm
您可能需要启动4个进程,然后每个进程使用不同的端口
这是启动了四个对话模型吧,如何让一个对话模型同时使用四张卡呢
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请问支持模型deepspeed大模型分割到不同显卡吗?
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Related Issues (20)
- 最后在执行python cli_demo.py chatglm时报错了(哪位大佬看看呀) HOT 1
- 执行python cli_demo.py chatglm报错客户端没有所需权限
- python cli_demo.py chatglm执行之后,输入用户之后报错,没有了后续结果 HOT 2
- cli_demo.py llama2报错
- chatglm第三个checkpoint超时 HOT 2
- 使用部署命令出现“'pangualpha' 不是内部或外部命令,也不是可运行的程序”错误 HOT 2
- 0.0.0.0:8000访问不了
- WSL2 ubuntu:python api.py chatglm = > RuntimeError
- would u support CUDA Version 12.2 ?
- python3 cli_demo.py chatglm 和 python web_demo.py chatglm部署遇到问题 HOT 1
- Building wheels for collected packages: tokenizers
- 无法部署OSError: [WinError 1314] 客户端没有所需的特权。: 'C:\\Users\\Administrator\\.cache\\jittor\\jt1.3.8\\cl\\py3.10.6\\Windows-10-10.x82\\IntelRCoreTMi3x81\\default\\checkpoints\\chat-glm/pytorch_model-00005-of-00008.bin' ->
- 安装依赖出现问题
- 换源
- 运行api.py之后,随着调用次数的增加,内存也在逐渐增加,最终直接内存占满自动被杀掉 HOT 2
- 无法运行
- 支持模型微调
- 无法启动web_demo.py & cli_demo.py 报错“import torch.utils.hooks as hooks ModuleNotFoundError: No module named 'torch.utils.hooks'” HOT 1
- 使用jittor.array时发生Cuda错误
- [BUG]如果用户名有空格,则程序执行时会出现错误
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