Image Feature Extraction
Transformers
Safetensors
aloe_dinov3_vision
feature-extraction
aloe
b-cos
interpretability
computer-vision
vision-transformer
cvpr-2026
custom_code
Instructions to use rmaser/aloe-dinov3-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rmaser/aloe-dinov3-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="rmaser/aloe-dinov3-large", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("rmaser/aloe-dinov3-large", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- cf0faef59e60cbd9594e718ec3ce3f601491be947e4c6b105fe23ec27d68a8a6
- Size of remote file:
- 988 kB
- SHA256:
- 7d9c11e1fae8401df4bfb159dc8c23b7afa1ef644fe133c3ce8e2cd948509c97
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