Instructions to use varcoder/Augmented-MIT-b5-new with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use varcoder/Augmented-MIT-b5-new with Transformers:
# Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("varcoder/Augmented-MIT-b5-new") model = SegformerForSemanticSegmentation.from_pretrained("varcoder/Augmented-MIT-b5-new", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9148ac3187fc6a7da98916dbce2c6415b301abd2147cc2c947853fb21e284214
- Size of remote file:
- 339 MB
- SHA256:
- 59924397d9b72cf37f4bbeee42fd3d415d866a8d3813f2ac79c01b7149978ab5
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