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:
- 9ee73eb8dd775ecacccca8c71b0545121e62ab380b7232c94312a0afc3df7e04
- Size of remote file:
- 14.2 MB
- SHA256:
- 32e01afa4c834b25a60ef221a04daca6dd817875d664807ca850a2e3ea9defcd
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