Instructions to use hf-internal-testing/tiny-random-MobileViTForSemanticSegmentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MobileViTForSemanticSegmentation with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, MobileViTForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-MobileViTForSemanticSegmentation") model = MobileViTForSemanticSegmentation.from_pretrained("hf-internal-testing/tiny-random-MobileViTForSemanticSegmentation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-internal-testing/tiny-random-MobileViTForSemanticSegmentation: direct link, hf CLI and curl.
- Browser
- Download file 25.5 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-MobileViTForSemanticSegmentation/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-MobileViTForSemanticSegmentation@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-MobileViTForSemanticSegmentation/resolve/refs%2Fpr%2F1/model.safetensors
25.5 MB
- Xet hash:
- 4281ef56750e7af5a8e3cae16f99002f02a44e0879fd583906a777df81b7c726
- Size of remote file:
- 25.5 MB
- SHA256:
- f6d53baa37f6234428c9acca3e51c8c82771c293403858423027a5fed7055488
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