Image Feature Extraction
Transformers
PyTorch
xmag
feature-extraction
pathology
histopathology
foundation-model
distillation
dinov2
custom_code
Instructions to use AI4PATH/XMAG with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AI4PATH/XMAG with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="AI4PATH/XMAG", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("AI4PATH/XMAG", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "model_type": "xmag", | |
| "architectures": [ | |
| "XMagModel" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "configuration_xmag.XMagConfig", | |
| "AutoModel": "modeling_xmag.XMagModel" | |
| }, | |
| "backbone_name": "dinov2_vitb14", | |
| "embed_dim": 768, | |
| "image_size": 224, | |
| "image_mean": [ | |
| 0.485, | |
| 0.456, | |
| 0.406 | |
| ], | |
| "image_std": [ | |
| 0.229, | |
| 0.224, | |
| 0.225 | |
| ], | |
| "expects_normalized_input": true, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.50.3" | |
| } | |