Instructions to use mwalmsley/baseline-encoder-classification-resnet50 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use mwalmsley/baseline-encoder-classification-resnet50 with timm:
import timm model = timm.create_model("hf-hub:mwalmsley/baseline-encoder-classification-resnet50", pretrained=True) - Notebooks
- Google Colab
- Kaggle
File size: 133 Bytes
620ae95 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:ed3f59e5577da683c073f4cffc2fdc6f5d7007ebfc76811280cfc8ab3351b836
size 94353602
|