Instructions to use timm/vit_large_patch14_dinov2.lvd142m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use timm/vit_large_patch14_dinov2.lvd142m with timm:
import timm model = timm.create_model("hf_hub:timm/vit_large_patch14_dinov2.lvd142m", pretrained=True) - Transformers
How to use timm/vit_large_patch14_dinov2.lvd142m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="timm/vit_large_patch14_dinov2.lvd142m")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("timm/vit_large_patch14_dinov2.lvd142m", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from timm/vit_large_patch14_dinov2.lvd142m: direct link, hf CLI and curl.
- Browser
- Download file 1.22 GB
-
https://huggingface.co/timm/vit_large_patch14_dinov2.lvd142m/resolve/main/model.safetensors
- Command line
-
hf download hf://timm/vit_large_patch14_dinov2.lvd142m/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/timm/vit_large_patch14_dinov2.lvd142m/resolve/main/model.safetensors
1.22 GB
- Xet hash:
- 4f7a85d60d103e5c931991b022c824fa19a19f9dc72f32e304c6a629cc547a49
- Size of remote file:
- 1.22 GB
- SHA256:
- 0424a5d1b515278cba3c6640ccbeaacc41de59d3a93df0dd5e494285eea2b355
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