Instructions to use jafdxc/regular-segmentation-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jafdxc/regular-segmentation-model with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("jafdxc/regular-segmentation-model") model = SegformerForSemanticSegmentation.from_pretrained("jafdxc/regular-segmentation-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from jafdxc/regular-segmentation-model: direct link, hf CLI and curl.
- Browser
- Download file 3.31 kB
-
https://huggingface.co/jafdxc/regular-segmentation-model/resolve/main/training_args.bin
- Command line
-
hf download hf://jafdxc/regular-segmentation-model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/jafdxc/regular-segmentation-model/resolve/main/training_args.bin
3.31 kB
- Xet hash:
- aad5269fa3055d5d88668b8e7c465e023f0ff3fe04c67ad5e51a3f88d6c16a2d
- Size of remote file:
- 3.31 kB
- SHA256:
- 97a9b7d8f1e1a66dcf6ce764aabb7e9ce9192d5007ff91baab3b004a3d374a8c
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