Instructions to use nielsr/sidewalk-semantic-demo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nielsr/sidewalk-semantic-demo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="nielsr/sidewalk-semantic-demo")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("nielsr/sidewalk-semantic-demo") model = SegformerForSemanticSegmentation.from_pretrained("nielsr/sidewalk-semantic-demo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from nielsr/sidewalk-semantic-demo: direct link, hf CLI and curl.
- Browser
- Download file 15 MB
-
https://huggingface.co/nielsr/sidewalk-semantic-demo/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://nielsr/sidewalk-semantic-demo/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/nielsr/sidewalk-semantic-demo/resolve/main/pytorch_model.bin
15 MB
- Xet hash:
- 616d86169c9299c50e6ff7c54dfc6cc25c1376fea5b2764918138a2e7a71f735
- Size of remote file:
- 15 MB
- SHA256:
- 0e748c1fc1837c2086048ced0c49ff7efe099772e30dd9d3e8b33b022bd9a15a
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