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", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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---
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tags:
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- image-classification
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- timm
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- transformers
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pipeline_tag: image-
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library_name: timm
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license: other
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license_name: dinov3-license
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doi = {10.5281/zenodo.4414861},
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howpublished = {\url{https://github.com/huggingface/pytorch-image-models}}
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}
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```
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---
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tags:
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- timm
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- transformers
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pipeline_tag: image-feature-extraction
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library_name: timm
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license: other
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license_name: dinov3-license
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doi = {10.5281/zenodo.4414861},
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howpublished = {\url{https://github.com/huggingface/pytorch-image-models}}
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}
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```
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