Instructions to use kevinvelez18/ViT_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kevinvelez18/ViT_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="kevinvelez18/ViT_model") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("kevinvelez18/ViT_model") model = AutoModelForImageClassification.from_pretrained("kevinvelez18/ViT_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 68e44be64220f0e8e90f8d3f51b56908127b7c6c8d194875d7e6a6e598a37307
- Size of remote file:
- 5.11 kB
- SHA256:
- 79b7dd1012600150b0cc0e89445ceedc5dadce418d77f61cfa62b515125a1f4e
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