Instructions to use hf-internal-testing/tiny-random-OneFormerForUniversalSegmentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-OneFormerForUniversalSegmentation with Transformers:
# Load model directly from transformers import AutoProcessor, OneFormerForUniversalSegmentation processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-OneFormerForUniversalSegmentation") model = OneFormerForUniversalSegmentation.from_pretrained("hf-internal-testing/tiny-random-OneFormerForUniversalSegmentation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 23ea6b8c45d383de1c2ee81233788976f51a0c50add4da0204415149da41eb2d
- Size of remote file:
- 47.9 MB
- SHA256:
- 4059e220e70259541ef1d8099782cf783022602dd2b0527d96d98fe0e74d606c
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