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:
- a5a5745e29e4138b72f426b7eb568cdeb61367a68d827accaa00fb92e0bf982b
- Size of remote file:
- 4.57 MB
- SHA256:
- ec430494c38d7ffec11b0398c2b614d3ecacefb27de9c018cf04c7c1c303f72f
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