Instructions to use hf-tiny-model-private/tiny-random-SegformerForSemanticSegmentation 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-SegformerForSemanticSegmentation with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-SegformerForSemanticSegmentation") model = SegformerForSemanticSegmentation.from_pretrained("hf-tiny-model-private/tiny-random-SegformerForSemanticSegmentation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hf-tiny-model-private/tiny-random-SegformerForSemanticSegmentation: direct link, hf CLI and curl.
- Browser
- Download file 4.36 MB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-SegformerForSemanticSegmentation/resolve/a008f2010856c9c3dd82a080634bcbabfaa04e43/pytorch_model.bin
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-SegformerForSemanticSegmentation@a008f2010856c9c3dd82a080634bcbabfaa04e43/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-tiny-model-private/tiny-random-SegformerForSemanticSegmentation/resolve/a008f2010856c9c3dd82a080634bcbabfaa04e43/pytorch_model.bin
4.36 MB
- Xet hash:
- 3e3d5bbba9e275b8dd3fe26902f550e0b99bacddf46d0048f7f349ebe8dabf2f
- Size of remote file:
- 4.36 MB
- SHA256:
- 00af69fa7ba660ba693cef5312b28fe4f10a4543d985e99993b1c46bf0495583
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