We read every piece of feedback, and take your input very seriously.
To see all available qualifiers, see our documentation.
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
使用示例代码进行推理,4bit的在回答的时候单张图像最大达到了38G的显存占用,是否是正常的。无量化的模型版本直接报错了。 from lmdeploy import TurbomindEngineConfig, pipeline from lmdeploy.vl import load_image engine_config = TurbomindEngineConfig(model_format='awq') pipe = pipeline('internlm/internlm-xcomposer2d5-7b-4bit', backend_config=engine_config) image = load_image('/root/workspace/InternLM-XComposer/examples/cars1.jpg') response = pipe(('describe this image', image)) print(response.text)
The text was updated successfully, but these errors were encountered:
The GPU memory usage is depended on the hd_num parameter (control the input image resolution).
hd_num
Sorry, something went wrong.
LightDXY
No branches or pull requests
使用示例代码进行推理,4bit的在回答的时候单张图像最大达到了38G的显存占用,是否是正常的。无量化的模型版本直接报错了。
from lmdeploy import TurbomindEngineConfig, pipeline
from lmdeploy.vl import load_image
engine_config = TurbomindEngineConfig(model_format='awq')
pipe = pipeline('internlm/internlm-xcomposer2d5-7b-4bit', backend_config=engine_config)
image = load_image('/root/workspace/InternLM-XComposer/examples/cars1.jpg')
response = pipe(('describe this image', image))
print(response.text)
The text was updated successfully, but these errors were encountered: