Instructions to use adhisetiawan/vit-resisc45 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adhisetiawan/vit-resisc45 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="adhisetiawan/vit-resisc45")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("adhisetiawan/vit-resisc45") model = AutoModel.from_pretrained("adhisetiawan/vit-resisc45") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 917c2d3c0aeb4ef6ec8277d8159ff9373511b78075be7dfc1a112688732fe737
- Size of remote file:
- 343 MB
- SHA256:
- cc0458920293abefd368dbf06c39112bb50c0477441ddec9a86fe09dcda93804
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