Instructions to use nommis/nommis_upernet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nommis/nommis_upernet with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, UperNetForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("nommis/nommis_upernet") model = UperNetForSemanticSegmentation.from_pretrained("nommis/nommis_upernet", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from nommis/nommis_upernet: direct link, hf CLI and curl.
- Browser
- Download file 4.03 kB
-
https://huggingface.co/nommis/nommis_upernet/resolve/main/training_args.bin
- Command line
-
hf download hf://nommis/nommis_upernet/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/nommis/nommis_upernet/resolve/main/training_args.bin
4.03 kB
- Xet hash:
- c7fbe479bfa48a950cfb85ce69d56b09ccd4b49b6f896e15d27a368af26177c5
- Size of remote file:
- 4.03 kB
- SHA256:
- 36c098e2bb3081e0cad43954251bcbca1f1e0c5d282ec97de7401aafcd0fe418
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