Instructions to use DataRaptor/custom-resnet50d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DataRaptor/custom-resnet50d with Transformers:
# Load model directly from transformers import AutoImageProcessor, ResnetModelForImageClassification processor = AutoImageProcessor.from_pretrained("DataRaptor/custom-resnet50d") model = ResnetModelForImageClassification.from_pretrained("DataRaptor/custom-resnet50d") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 79ca294ed71f038e42d54b6598b90cbbde9d8ba00ba4806b3a6683f6565721c2
- Size of remote file:
- 103 MB
- SHA256:
- 4a945a1d4bcb0c80f4a944dd77dc32441d39c2c06fa67d650e9a9090fde8934b
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