Instructions to use timm/vit_base_patch14_dinov2.lvd142m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use timm/vit_base_patch14_dinov2.lvd142m with timm:
import timm model = timm.create_model("hf_hub:timm/vit_base_patch14_dinov2.lvd142m", pretrained=True) - Transformers
How to use timm/vit_base_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_base_patch14_dinov2.lvd142m")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("timm/vit_base_patch14_dinov2.lvd142m", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6349d1fa4c2d9023a1c003193101e269bd1ece9bf90cc37e977adc1bc665628b
- Size of remote file:
- 346 MB
- SHA256:
- c8f07b5edc5f37f0ec8205fd8777d8c594281d05fc7abd4569f273ea3838e4d6
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