Instructions to use seige-ml/DERETFound_GREEN with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use seige-ml/DERETFound_GREEN with timm:
import timm model = timm.create_model("hf-hub:seige-ml/DERETFound_GREEN", pretrained=True) - Notebooks
- Google Colab
- Kaggle
Download config.json from seige-ml/DERETFound_GREEN: direct link, hf CLI and curl.
- Browser
- Download file 606 Bytes
-
https://huggingface.co/seige-ml/DERETFound_GREEN/resolve/80047e10643579c9378278dda42a2d9eadae16bd/config.json
- Command line
-
hf download hf://seige-ml/DERETFound_GREEN@80047e10643579c9378278dda42a2d9eadae16bd/config.json
-
curl -L -o config.json https://huggingface.co/seige-ml/DERETFound_GREEN/resolve/80047e10643579c9378278dda42a2d9eadae16bd/config.json
606 Bytes
| { | |
| "architecture": "vit_small_patch14_reg4_dinov2", | |
| "num_classes": 0, | |
| "num_features": 384, | |
| "global_pool": "token", | |
| "pretrained_cfg": { | |
| "tag": "lvd142m", | |
| "custom_load": false, | |
| "input_size": [ | |
| 3, | |
| 392, | |
| 392 | |
| ], | |
| "fixed_input_size": true, | |
| "interpolation": "bicubic", | |
| "crop_pct": 1.0, | |
| "crop_mode": "center", | |
| "mean": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "std": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "num_classes": 0, | |
| "pool_size": null, | |
| "first_conv": "patch_embed.proj", | |
| "classifier": "head", | |
| "license": "apache-2.0" | |
| } | |
| } |