Instructions to use hf-internal-testing/tiny-random-SegformerForSemanticSegmentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-SegformerForSemanticSegmentation with Transformers:
# Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-SegformerForSemanticSegmentation") model = SegformerForSemanticSegmentation.from_pretrained("hf-internal-testing/tiny-random-SegformerForSemanticSegmentation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 22c590ff7a483abeb00ba8808144817f4e20aff2a2aa87a2b6ba33b267c12596
- Size of remote file:
- 4.36 MB
- SHA256:
- 90ecfb3c0f0249f27b1b930bc0da73ebe0ee57d7266dd6cd332f1234c48dc50f
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