Instructions to use microsoft/rad-dino with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/rad-dino with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="microsoft/rad-dino")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("microsoft/rad-dino") model = AutoModel.from_pretrained("microsoft/rad-dino") - Notebooks
- Google Colab
- Kaggle
Add files helpful for fine-tuning
#6
by fepegar - opened
Adding extra files to help users fine-tune RAD-DINO:
- DINO head weights
- Backbone weights compatible with the code in the DINOv2 repo
- Config files and Python module with many hyperparameters
fepegar changed pull request status to merged
fepegar changed pull request title from Update README.md to Add files helpful for fine-tuning