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")
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Sacbe/ViT_SAM_Classification", device_map="auto")
https://huggingface.co/Sacbe/ViT_SAM_Classification/resolve/main/ViT_B16(SAM)__Classification.ipynb
hf download 'hf://Sacbe/ViT_SAM_Classification/ViT_B16(SAM)__Classification.ipynb'
curl -L -o 'ViT_B16(SAM)__Classification.ipynb' 'https://huggingface.co/Sacbe/ViT_SAM_Classification/resolve/main/ViT_B16(SAM)__Classification.ipynb'
