Instructions to use zuppif/resnet-d-50 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zuppif/resnet-d-50 with Transformers:
# Load model directly from transformers import ResNetDForImageClassification model = ResNetDForImageClassification.from_pretrained("zuppif/resnet-d-50", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7f268b7fb4f79a492253321faec16ba5a463a4dd2add5988838300f477811679
- Size of remote file:
- 103 MB
- SHA256:
- 96cfab4f6a4fa18b10871c5d66d5de1540cc04bd1b1d95bc4142a39666f29f53
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