Instructions to use akar49/Maskformer-MRIseg_model-Sep with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use akar49/Maskformer-MRIseg_model-Sep with Transformers:
# Load model directly from transformers import AutoImageProcessor, MaskFormerForInstanceSegmentation processor = AutoImageProcessor.from_pretrained("akar49/Maskformer-MRIseg_model-Sep") model = MaskFormerForInstanceSegmentation.from_pretrained("akar49/Maskformer-MRIseg_model-Sep", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c3e3f45022d5dd46ca0c8282560069e447eb152ae95505c46d88b8f6a5fd8d81
- Size of remote file:
- 411 MB
- SHA256:
- bc50e5f6efebfa3f851b9de1dd44be5474a33328f9af1c79e241e60649b31941
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.