Feature Extraction
Transformers
PyTorch
Safetensors
English
vit
image-feature-extraction
biology
medical
cancer
Instructions to use owkin/phikon with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use owkin/phikon with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="owkin/phikon")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("owkin/phikon") model = AutoModel.from_pretrained("owkin/phikon") - Inference
- Notebooks
- Google Colab
- Kaggle
Update `layer_norm_eps` to match timm
#1
by 1aurent - opened
- config.json +1 -1
config.json
CHANGED
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@@ -10,7 +10,7 @@
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"image_size": 224,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"layer_norm_eps": 1e-
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"model_type": "vit",
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"num_attention_heads": 12,
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"num_channels": 3,
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"image_size": 224,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"layer_norm_eps": 1e-6,
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"model_type": "vit",
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"num_attention_heads": 12,
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"num_channels": 3,
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