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
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:130709b16fa9256d1d9544f43fb686d278e8177c1bd8876907ce5788246b6e06
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size 94273440
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