Instructions to use timm/convnext_tiny.dinov3_lvd1689m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use timm/convnext_tiny.dinov3_lvd1689m with timm:
import timm model = timm.create_model("hf_hub:timm/convnext_tiny.dinov3_lvd1689m", pretrained=True) - Transformers
How to use timm/convnext_tiny.dinov3_lvd1689m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="timm/convnext_tiny.dinov3_lvd1689m")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("timm/convnext_tiny.dinov3_lvd1689m", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 08dcbf690ac8c31c75234212d44d60cdcf73fd3bee1cbf08eae3fe3c3523b301
- Size of remote file:
- 111 MB
- SHA256:
- 1a1459312019fa97c3508b56d7985f2a7e53e85bbf7b3ca027b2e44709bb4837
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