Instructions to use hf-internal-testing/tiny-random-MobileNetV2ForSemanticSegmentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MobileNetV2ForSemanticSegmentation with Transformers:
# Load model directly from transformers import AutoImageProcessor, MobileNetV2ForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-MobileNetV2ForSemanticSegmentation") model = MobileNetV2ForSemanticSegmentation.from_pretrained("hf-internal-testing/tiny-random-MobileNetV2ForSemanticSegmentation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7d4c80895e92d984025fce7ba57381a6e432552ee2867539d04db1a7d379a6fe
- Size of remote file:
- 1.81 MB
- SHA256:
- c9589441412be2f9087ccf726fdc304320c9ae9e7a60baa9f3f651a61d3443be
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