Instructions to use hf-internal-testing/tiny-random-MobileViTV2ForSemanticSegmentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MobileViTV2ForSemanticSegmentation with Transformers:
# Load model directly from transformers import AutoImageProcessor, MobileViTV2ForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-MobileViTV2ForSemanticSegmentation") model = MobileViTV2ForSemanticSegmentation.from_pretrained("hf-internal-testing/tiny-random-MobileViTV2ForSemanticSegmentation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5b8826ce739ee5d59a3df61f2271893bc86e44128212ac2c20da25bb6fd3ecbf
- Size of remote file:
- 14.2 MB
- SHA256:
- 4b568175851d2eaf5ffb658fad9a283a0f9fede37eb3cda359467f8197e6f6f3
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