Instructions to use timm/vit_giant_patch14_reg4_dinov2.lvd142m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use timm/vit_giant_patch14_reg4_dinov2.lvd142m with timm:
import timm model = timm.create_model("hf-hub:timm/vit_giant_patch14_reg4_dinov2.lvd142m", pretrained=True) - Transformers
How to use timm/vit_giant_patch14_reg4_dinov2.lvd142m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="timm/vit_giant_patch14_reg4_dinov2.lvd142m")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("timm/vit_giant_patch14_reg4_dinov2.lvd142m", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from timm/vit_giant_patch14_reg4_dinov2.lvd142m: direct link, hf CLI and curl.
- Browser
- Download file 4.55 GB
-
https://huggingface.co/timm/vit_giant_patch14_reg4_dinov2.lvd142m/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://timm/vit_giant_patch14_reg4_dinov2.lvd142m/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/timm/vit_giant_patch14_reg4_dinov2.lvd142m/resolve/main/pytorch_model.bin
4.55 GB
- Xet hash:
- 2c22384b1a3fc59007cc260cc3886743db401e63469cbd81b39b35f0838f5845
- Size of remote file:
- 4.55 GB
- SHA256:
- 302f2ce93076318108f94bc8549661c6f9a2a357f7934c447f97d7ff6b08a852
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