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:
- 527731da0d0076428a58847953b4566a1dc59e467837505e54973c86c2e65c90
- Size of remote file:
- 47.4 MB
- SHA256:
- a9b4954ba7a86a160ee9e830d3768e2bdd8027f3f44108d3052494fa696e07bb
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