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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- acbd62f681be027bed80b48ccb9bbf6f12f0291ac5ddf558eeda72e1a9cd6f17
- Size of remote file:
- 4.32 MB
- SHA256:
- 08bc55a47607d1702dbd8627561d78ac9d29489ffacef2da06696d1b067e7747
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