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:
- 27229f56d02925b1665cf2e7d20b911d88f8951512ecc5ad98cb367683cf786a
- Size of remote file:
- 47.8 MB
- SHA256:
- d59c5c8b90be1ea6eeb929d56fa5b06eaa6277670ce6b88a79fd0bb1c11f810a
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