Instructions to use sumba/deit_base_other_classes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sumba/deit_base_other_classes with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="sumba/deit_base_other_classes")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("sumba/deit_base_other_classes") model = AutoModel.from_pretrained("sumba/deit_base_other_classes") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a55677a1aa0345015b56099bdffedc32ccf53cfcd0cb0ef11d340f756b137106
- Size of remote file:
- 346 MB
- SHA256:
- 410c0bb5a067f66b6de8ed5b9f90e2ab0a2550bcd191ad39414d80ad35971dac
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