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:
- aa4fbfe35ae76afdd595b63c70f9a2874ddd994a9a8ba207a5d95370b7c52d20
- Size of remote file:
- 1.74 MB
- SHA256:
- 616eb026aefce1d2d514636a58149b7c39d892ad95c60c635c9d9f1a86694bb6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.