Instructions to use Jfeagans89/regular-segmentation-model-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jfeagans89/regular-segmentation-model-v2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("Jfeagans89/regular-segmentation-model-v2") model = SegformerForSemanticSegmentation.from_pretrained("Jfeagans89/regular-segmentation-model-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Jfeagans89/regular-segmentation-model-v2: direct link, hf CLI and curl.
- Browser
- Download file 14.9 MB
-
https://huggingface.co/Jfeagans89/regular-segmentation-model-v2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Jfeagans89/regular-segmentation-model-v2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Jfeagans89/regular-segmentation-model-v2/resolve/main/pytorch_model.bin
14.9 MB
- Xet hash:
- 2725bc6b415bfadf3802539ac2f2cf42c493afdd2fd9a3a6ffdafb58d5c4460d
- Size of remote file:
- 14.9 MB
- SHA256:
- 50fcf62bf0144a45448386dff64098896563cd1e1b4e8bdf5ece8017b5309ce1
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