Instructions to use m3/sscd-copy-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use m3/sscd-copy-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="m3/sscd-copy-detection")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("m3/sscd-copy-detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "size": 288, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.485, | |
| 0.456, | |
| 0.406 | |
| ], | |
| "image_processor_type": "SscdImageProcessor", | |
| "image_std": [ | |
| 0.229, | |
| 0.224, | |
| 0.225 | |
| ], | |
| "do_convert_rgb": true | |
| } | |