Instructions to use hf-tiny-model-private/tiny-random-UperNetForSemanticSegmentation 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-UperNetForSemanticSegmentation with Transformers:
# Load model directly from transformers import AutoImageProcessor, UperNetForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-UperNetForSemanticSegmentation") model = UperNetForSemanticSegmentation.from_pretrained("hf-tiny-model-private/tiny-random-UperNetForSemanticSegmentation") - Notebooks
- Google Colab
- Kaggle
File size: 2,981 Bytes
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