Instructions to use timm/vit_small_patch16_224.dino with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use timm/vit_small_patch16_224.dino with timm:
import timm model = timm.create_model("hf-hub:timm/vit_small_patch16_224.dino", pretrained=True) - Transformers
How to use timm/vit_small_patch16_224.dino with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="timm/vit_small_patch16_224.dino")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("timm/vit_small_patch16_224.dino", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from timm/vit_small_patch16_224.dino: direct link, hf CLI and curl.
- Browser
- Download file 86.7 MB
-
https://huggingface.co/timm/vit_small_patch16_224.dino/resolve/main/model.safetensors
- Command line
-
hf download hf://timm/vit_small_patch16_224.dino/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/timm/vit_small_patch16_224.dino/resolve/main/model.safetensors
86.7 MB
- Xet hash:
- 945de9402831cfebbab8838f55fee277b724b16795eceb073174cb03297508f1
- Size of remote file:
- 86.7 MB
- SHA256:
- 8d4795b8e4e327c6d841e15a2e3e6d88c45346256a43f8cdae8c26d92c806f7a
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