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:
- 5509f00e9df4e4e32fab9e8898f9cde714da699c4f9ae23b53004cbc7f99736c
- Size of remote file:
- 4.57 MB
- SHA256:
- ffd7a451052f68afd2bce719900b32e2af032940c70fd82ad7fa3a132c2b5c50
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