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:
- 705dc8311a5edcbfa6b712e59dacf2cd5a1186e44c65a9dff4a8cb19c242b02b
- Size of remote file:
- 14.2 MB
- SHA256:
- 9bf9ea85c4475c1fe287f52db5209c71a7e4e9d87c4123d73af1caf075cea6e8
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