Instructions to use hf-tiny-model-private/tiny-random-SegformerForSemanticSegmentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-SegformerForSemanticSegmentation with Transformers:
# Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-SegformerForSemanticSegmentation") model = SegformerForSemanticSegmentation.from_pretrained("hf-tiny-model-private/tiny-random-SegformerForSemanticSegmentation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3e3d5bbba9e275b8dd3fe26902f550e0b99bacddf46d0048f7f349ebe8dabf2f
- Size of remote file:
- 4.36 MB
- SHA256:
- 00af69fa7ba660ba693cef5312b28fe4f10a4543d985e99993b1c46bf0495583
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