Instructions to use KevinCha/dinov2-base-register with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KevinCha/dinov2-base-register with Transformers:
# Load model directly from transformers import Dinov2VisionTransformer model = Dinov2VisionTransformer.from_pretrained("KevinCha/dinov2-base-register", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "act_layer": "nn.GELU", | |
| "architectures": [ | |
| "Dinov2VisionTransformer" | |
| ], | |
| "block_chunks": 0, | |
| "depth": 12, | |
| "drop_path_rate": 0.0, | |
| "drop_path_uniform": false, | |
| "dtype": "float32", | |
| "embed_dim": 768, | |
| "ffn_bias": true, | |
| "ffn_layer": "mlp", | |
| "img_size": 518, | |
| "in_chans": 3, | |
| "init_values": 1e-05, | |
| "interpolate_antialias": false, | |
| "interpolate_offset": 0.1, | |
| "mlp_ratio": 4.0, | |
| "num_heads": 12, | |
| "num_register_tokens": 4, | |
| "output_indices": [ | |
| 2, | |
| 5, | |
| 8, | |
| 11 | |
| ], | |
| "patch_size": 14, | |
| "proj_bias": true, | |
| "qkv_bias": true, | |
| "transformers_version": "4.57.3" | |
| } | |