Instructions to use buddhadeb33/outputs_dinov3_Feb_2026 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use buddhadeb33/outputs_dinov3_Feb_2026 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("buddhadeb33/outputs_dinov3_Feb_2026", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7174df512f5659c97787a4fc37c7f5d193e5e4aac60d6f59772c43fb588f7d35
- Size of remote file:
- 5.2 kB
- SHA256:
- 4237a7ff7cc4ca17ad947597aff44056bfcf92b840d161b6b2f75d2cd9c64855
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