
ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders: https://arxiv.org/abs/2301.00808

Pre-Trained Model from timm-library: https://huggingface.co/timm/convnextv2_base.fcmae_ft_in22k_in1k_384

INaturalist-21 fine-tune dataset: https://github.com/visipedia/inat_comp/tree/master/2021


## References:
Sanghyun Woo, I., & Saining Xie (2023). ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders. arXiv preprint arXiv:2301.00808.

Ross Wightman. (2019). PyTorch Image Models.
{"datasets": ["inaturalist-21"]}
dataset:inaturalist-21 arxiv:2301.00808 region:us
TAGS
#dataset-inaturalist-21 #arxiv-2301.00808 #region-us 


ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders: URL

Pre-Trained Model from timm-library: URL

INaturalist-21 fine-tune dataset: URL


## References:
Sanghyun Woo, I., & Saining Xie (2023). ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders. arXiv preprint arXiv:2301.00808.

Ross Wightman. (2019). PyTorch Image Models.
## References:
Sanghyun Woo, I., & Saining Xie (2023). ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders. arXiv preprint arXiv:2301.00808.

Ross Wightman. (2019). PyTorch Image Models.
TAGS
#dataset-inaturalist-21 #arxiv-2301.00808 #region-us 
 ## References:
Sanghyun Woo, I., & Saining Xie (2023). ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders. arXiv preprint arXiv:2301.00808.

Ross Wightman. (2019). PyTorch Image Models.
TAGS
#dataset-inaturalist-21 #arxiv-2301.00808 #region-us 
## References:
Sanghyun Woo, I., & Saining Xie (2023). ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders. arXiv preprint arXiv:2301.00808.

Ross Wightman. (2019). PyTorch Image Models.