Image Classification
timm
Safetensors
PyTorch
brain-mri
tumor-detection
out-of-distribution
medical-imaging
benchmark
Instructions to use Fatihaybasn/brainmri-ood-efficientnet-b0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use Fatihaybasn/brainmri-ood-efficientnet-b0 with timm:
import timm model = timm.create_model("hf_hub:Fatihaybasn/brainmri-ood-efficientnet-b0", pretrained=True) - Notebooks
- Google Colab
- Kaggle
| { | |
| "project": "Brain MRI Tumor vs No-Tumor - OOD Generalization (10 Models)", | |
| "architecture": "efficientnet_b0", | |
| "variant": "efficientnet_b0", | |
| "num_classes": 2, | |
| "id2label": { | |
| "0": "no_tumor", | |
| "1": "tumor" | |
| }, | |
| "label2id": { | |
| "no_tumor": 0, | |
| "tumor": 1 | |
| }, | |
| "input_size": 224, | |
| "preprocessing": { | |
| "square_pad": true, | |
| "resize": [ | |
| 224, | |
| 224 | |
| ], | |
| "mean": [ | |
| 0.485, | |
| 0.456, | |
| 0.406 | |
| ], | |
| "std": [ | |
| 0.229, | |
| 0.224, | |
| 0.225 | |
| ] | |
| }, | |
| "decision_threshold": 0.5, | |
| "augmentation_strength": 0.0, | |
| "github_repository": "https://github.com/fatihaybsn/BrainMRI-OOD-10Models", | |
| "github_commit": "a9920408189230b886773a64d113eb35bcba1971", | |
| "original_checkpoint_sha256": "f097f292733603a5030e74b5398e333633c8055b9666871e376f67493f2475fc", | |
| "safetensors_sha256": "ea7802bee8ce10223ed169540513cdccc4865218aeb1cd49f8f541ae9cf30a75", | |
| "metrics": { | |
| "accuracy": 0.6925914540424224, | |
| "auc": 0.902755710499151, | |
| "f1": 0.567847882454624, | |
| "recall_sensitivity": 0.3969788519637462, | |
| "precision": 0.9969650986342944, | |
| "kappa": 0.3915249697352413 | |
| } | |
| } | |