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:
# pip install -U transformers accelerate # 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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-tiny-model-private/tiny-random-MobileNetV2ForSemanticSegmentation: direct link, hf CLI and curl.
- Browser
- Download file 1.74 MB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-MobileNetV2ForSemanticSegmentation/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-MobileNetV2ForSemanticSegmentation@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-tiny-model-private/tiny-random-MobileNetV2ForSemanticSegmentation/resolve/refs%2Fpr%2F1/model.safetensors
1.74 MB
- Xet hash:
- aa4fbfe35ae76afdd595b63c70f9a2874ddd994a9a8ba207a5d95370b7c52d20
- Size of remote file:
- 1.74 MB
- SHA256:
- 616eb026aefce1d2d514636a58149b7c39d892ad95c60c635c9d9f1a86694bb6
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