Feature Extraction
Transformers
Safetensors
English
spectre
medical-imaging
ct-scan
3d
vision-transformer
self-supervised-learning
foundation-model
radiology
custom_code
Instructions to use cclaess/SPECTRE-Large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cclaess/SPECTRE-Large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="cclaess/SPECTRE-Large", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("cclaess/SPECTRE-Large", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| from .vision_transformer import ( | |
| VisionTransformer, | |
| vit_tiny_patch16_128, | |
| vit_small_patch16_128, | |
| vit_base_patch16_128, | |
| vit_base_patch32_128, | |
| vit_large_patch16_128, | |
| vit_large_patch32_128, | |
| ) | |
| from .vision_transformer_features import ( | |
| FeatureVisionTransformer, | |
| feat_vit_tiny, | |
| feat_vit_small, | |
| feat_vit_base, | |
| feat_vit_large, | |
| ) | |
| __all__ = [ | |
| 'VisionTransformer', | |
| 'vit_tiny_patch16_128', | |
| 'vit_small_patch16_128', | |
| 'vit_base_patch16_128', | |
| 'vit_base_patch32_128', | |
| 'vit_large_patch16_128', | |
| 'vit_large_patch32_128', | |
| 'FeatureVisionTransformer', | |
| 'feat_vit_tiny', | |
| 'feat_vit_small', | |
| 'feat_vit_base', | |
| 'feat_vit_large', | |
| ] | |