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:
- fcc9e7a20905af14c3d04bb578e816670b0c30b37f0ed34b361810262d19108a
- Size of remote file:
- 14.2 MB
- SHA256:
- cebd886a9e7a4266331505c55ea273703c2c03c4a3c7407e0ca905fa21b8bdee
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