Instructions to use hf-tiny-model-private/tiny-random-MobileViTForSemanticSegmentation 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-MobileViTForSemanticSegmentation with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, MobileViTForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-MobileViTForSemanticSegmentation") model = MobileViTForSemanticSegmentation.from_pretrained("hf-tiny-model-private/tiny-random-MobileViTForSemanticSegmentation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hf-tiny-model-private/tiny-random-MobileViTForSemanticSegmentation: direct link, hf CLI and curl.
- Browser
- Download file 25.6 MB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-MobileViTForSemanticSegmentation/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-MobileViTForSemanticSegmentation/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-tiny-model-private/tiny-random-MobileViTForSemanticSegmentation/resolve/main/pytorch_model.bin
25.6 MB
- Xet hash:
- 4689d175540ee119e4e2861b3dae4d14b8263bb18d5203705a63131c705e13e9
- Size of remote file:
- 25.6 MB
- SHA256:
- 07602737986c323c9b46e490eb0c9d5112d1bed3327e18398a2b3a36e815eb5e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.