Instructions to use lucasdmpp/streetSegmentation-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lucasdmpp/streetSegmentation-model with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("lucasdmpp/streetSegmentation-model") model = SegformerForSemanticSegmentation.from_pretrained("lucasdmpp/streetSegmentation-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from lucasdmpp/streetSegmentation-model: direct link, hf CLI and curl.
- Browser
- Download file 15.1 MB
-
https://huggingface.co/lucasdmpp/streetSegmentation-model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://lucasdmpp/streetSegmentation-model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/lucasdmpp/streetSegmentation-model/resolve/main/pytorch_model.bin
15.1 MB
- Xet hash:
- 62565f689c9cdadbd08e77ca1b30873531e5cd04ba286132787fcfd8e4ea3ef5
- Size of remote file:
- 15.1 MB
- SHA256:
- 9e873f3b41c03ad00a36e261060f9fd576043d5a700cf528d8aa631b65f89748
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