Instructions to use rwood-97/test_os_counties with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rwood-97/test_os_counties with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="rwood-97/test_os_counties")# Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("rwood-97/test_os_counties") model = SegformerForSemanticSegmentation.from_pretrained("rwood-97/test_os_counties", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from rwood-97/test_os_counties: direct link, hf CLI and curl.
- Browser
- Download file 14.9 MB
-
https://huggingface.co/rwood-97/test_os_counties/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://rwood-97/test_os_counties/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/rwood-97/test_os_counties/resolve/main/pytorch_model.bin
14.9 MB
- Xet hash:
- 9ae1e87524a6a41517fe5d96cac001658d6e8b35fbe9690c40e142093e0db5fd
- Size of remote file:
- 14.9 MB
- SHA256:
- 0f9cd30ecc2f84d626e1f39e7a9d53a12aa7705afc17c27d5016a06030eb84e2
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