Instructions to use facebook/maskformer-resnet50-ade with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/maskformer-resnet50-ade with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, MaskFormerForInstanceSegmentation processor = AutoImageProcessor.from_pretrained("facebook/maskformer-resnet50-ade") model = MaskFormerForInstanceSegmentation.from_pretrained("facebook/maskformer-resnet50-ade", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from facebook/maskformer-resnet50-ade: direct link, hf CLI and curl.
- Browser
- Download file 166 MB
-
https://huggingface.co/facebook/maskformer-resnet50-ade/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://facebook/maskformer-resnet50-ade/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/facebook/maskformer-resnet50-ade/resolve/main/pytorch_model.bin
166 MB
- Xet hash:
- 5db7aa142f97a6112cdb8bbfb47a3c2c5a20393568d9d88467d3882c9d67f403
- Size of remote file:
- 166 MB
- SHA256:
- 715296aae42e9dcf138eb3254fedd308df2d24fe5c189797874ca028a461ceff
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