Instructions to use hf-tiny-model-private/tiny-random-MobileNetV2ForSemanticSegmentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-MobileNetV2ForSemanticSegmentation with Transformers:
# Load model directly from transformers import AutoImageProcessor, MobileNetV2ForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-MobileNetV2ForSemanticSegmentation") model = MobileNetV2ForSemanticSegmentation.from_pretrained("hf-tiny-model-private/tiny-random-MobileNetV2ForSemanticSegmentation") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 73e5cad6b149bf788a06a6bb5de210d9e7a3264e48e20bbd33eea2ba5e0d11db
- Size of remote file:
- 1.81 MB
- SHA256:
- 3a78c1f1c100a4c48cd452af850003d1e5bdfdd27a9062df6048f0fbb37b1de1
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