Instructions to use timm/vit_large_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_large_patch14_reg4_dinov2.lvd142m with timm:
import timm model = timm.create_model("hf_hub:timm/vit_large_patch14_reg4_dinov2.lvd142m", pretrained=True) - Transformers
How to use timm/vit_large_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_large_patch14_reg4_dinov2.lvd142m")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("timm/vit_large_patch14_reg4_dinov2.lvd142m", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- de628f6a271dff77f7068906f960b4be293e9063d8e5e680359ac73c67498291
- Size of remote file:
- 1.22 GB
- SHA256:
- 78971dc00a0c488f2b2dff17d6dcb7ebe787af70a703d8212b38fc6a33dbcdd4
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