Instructions to use mwalmsley/baseline-encoder-regression-convnext_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use mwalmsley/baseline-encoder-regression-convnext_base with timm:
import timm model = timm.create_model("hf_hub:mwalmsley/baseline-encoder-regression-convnext_base", pretrained=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cd0d2dcfae5627d08603acc41275e7640708769a347509da0dd4c40def6bf3af
- Size of remote file:
- 350 MB
- SHA256:
- 89b1542e30d5dd0e341bea3df1fc53fd3a3793061ad74c76c9edac7bcb0f6555
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