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
File size: 475 Bytes
240df91 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | {
"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
} |