Instructions to use mwalmsley/zoobot-encoder-convnext_nano with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use mwalmsley/zoobot-encoder-convnext_nano with timm:
import timm model = timm.create_model("hf-hub:mwalmsley/zoobot-encoder-convnext_nano", pretrained=True) - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from mwalmsley/zoobot-encoder-convnext_nano: direct link, hf CLI and curl.
- Browser
- Download file 59.9 MB
-
https://huggingface.co/mwalmsley/zoobot-encoder-convnext_nano/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://mwalmsley/zoobot-encoder-convnext_nano/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/mwalmsley/zoobot-encoder-convnext_nano/resolve/main/pytorch_model.bin
59.9 MB
- Xet hash:
- c2a545e534c5167e0b710bf7d05baafe5ef268ae6e2bc1ee9858d5fdc282dbbf
- Size of remote file:
- 59.9 MB
- SHA256:
- 7a98bb967704d827f5c7611261e7064d7b475fa13af5602ac1a782e15e4df1cc
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