Table of Contents
Shortcuts

# convnext_base

torchvision.models.convnext_base(*, weights: Optional[ConvNeXt_Base_Weights] = None, progress: bool = True, **kwargs: Any) → ConvNeXt

  ConvNeXt Base model architecture from the A ConvNet for the 2020s paper.

  Parameters:

    - weights (`ConvNeXt_Base_Weights`, optional) – The pretrained weights to use. See `ConvNeXt_Base_Weights` below for more details and possible values. By default, no pre-trained weights are used.

    - progress (bool, optional) – If True, displays a progress bar of the download to stderr. Default is True.

    - **kwargs – parameters passed to the `torchvision.models.convnext.ConvNext` base class. Please refer to the source code for more details about this class.

  class torchvision.models.ConvNeXt_Base_Weights(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)

## Docs

Access comprehensive developer documentation for PyTorch

View Docs

## Tutorials

Get in-depth tutorials for beginners and advanced developers

View Tutorials

## Resources

Find development resources and get your questions answered

View Resources

To analyze traffic and optimize your experience, we serve cookies on this site. By clicking or navigating, you agree to allow our usage of cookies. As the current maintainers of this site, Facebook’s Cookies Policy applies. Learn more, including about available controls: Cookies Policy.