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:
# pip install -U transformers accelerate # 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
Download model.safetensors from hf-internal-testing/tiny-random-MobileNetV2ForSemanticSegmentation: direct link, hf CLI and curl.
- Browser
- Download file 1.74 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-MobileNetV2ForSemanticSegmentation/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-MobileNetV2ForSemanticSegmentation@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-MobileNetV2ForSemanticSegmentation/resolve/refs%2Fpr%2F1/model.safetensors
1.74 MB
- Xet hash:
- 520d5c4510f31001a526fe598f7036f33021d86167ea2820187e15b4893372c4
- Size of remote file:
- 1.74 MB
- SHA256:
- 8ef07c17e7854308e34d8ddf45004b40266e196ae6a4939abb14a4ad786b8ec8
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