Instructions to use timm/vit_small_patch14_dinov2.lvd142m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use timm/vit_small_patch14_dinov2.lvd142m with timm:
import timm model = timm.create_model("hf_hub:timm/vit_small_patch14_dinov2.lvd142m", pretrained=True) - Transformers
How to use timm/vit_small_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_small_patch14_dinov2.lvd142m")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("timm/vit_small_patch14_dinov2.lvd142m", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3ac9ab511845e46d408d4eb9defb81e703a14178c88fb70c9bbf159d35637d67
- Size of remote file:
- 88.3 MB
- SHA256:
- 120606d7ac0927e8fe3661d1f0f6705f80e5202203547e79d7d88d9bfa80e648
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