Instructions to use deepang/adaptformer-LEVIR-CD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepang/adaptformer-LEVIR-CD with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="deepang/adaptformer-LEVIR-CD", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("deepang/adaptformer-LEVIR-CD", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "auto_map": { | |
| "AutoImageProcessor": "preprocessing_adaptformer.AdaptFormerImageProcessor" | |
| }, | |
| "size": 256, | |
| "do_center_crop": false, | |
| "do_convert_rgb": true, | |
| "do_normalize": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.485, | |
| 0.456, | |
| 0.406 | |
| ], | |
| "image_processor_type": "AdaptFormerImageProcessor", | |
| "image_std": [ | |
| 0.229, | |
| 0.224, | |
| 0.225 | |
| ], | |
| "resample": 3 | |
| } |