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)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("AI4PATH/XMAG", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 470 Bytes
c849cf3 0fcabb3 c849cf3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | {
"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"
}
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