Instructions to use Sacbe/ViT_SAM_Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sacbe/ViT_SAM_Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Sacbe/ViT_SAM_Classification") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Sacbe/ViT_SAM_Classification", dtype="auto") - Notebooks
- Google Colab
- Kaggle
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# Resultados obtenidos
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<img src="https://cdn-uploads.huggingface.co/production/uploads/64ff2131f7f3fa2d7fe256fc/CO6vFEjt3FkxB8JgZTbEd.png" width="
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# Resultados obtenidos
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<img src="https://cdn-uploads.huggingface.co/production/uploads/64ff2131f7f3fa2d7fe256fc/CO6vFEjt3FkxB8JgZTbEd.png" width="500" />
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