Instructions to use hf-internal-testing/tiny-random-Mask2FormerForUniversalSegmentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Mask2FormerForUniversalSegmentation with Transformers:
# Load model directly from transformers import AutoImageProcessor, Mask2FormerForUniversalSegmentation processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-Mask2FormerForUniversalSegmentation") model = Mask2FormerForUniversalSegmentation.from_pretrained("hf-internal-testing/tiny-random-Mask2FormerForUniversalSegmentation") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 150405be1a3e188e9b506692811af271d02fb64420a13ff045934757060b4063
- Size of remote file:
- 47.3 MB
- SHA256:
- fe98d3ebd9c7a71fd26833b6caa1f7ae893ab4b9069799e9dcbca0620314c6c3
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