Instructions to use amosr2002/amazing_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amosr2002/amazing_model with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("amosr2002/amazing_model") model = SegformerForSemanticSegmentation.from_pretrained("amosr2002/amazing_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from amosr2002/amazing_model: direct link, hf CLI and curl.
- Browser
- Download file 3.39 kB
-
https://huggingface.co/amosr2002/amazing_model/resolve/main/training_args.bin
- Command line
-
hf download hf://amosr2002/amazing_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/amosr2002/amazing_model/resolve/main/training_args.bin
3.39 kB
- Xet hash:
- 541320800e7651795a00a3e314a1600c10f6e2a36bbf25578d0ddc82b4158dfb
- Size of remote file:
- 3.39 kB
- SHA256:
- e89f2ca463ef9e28defca995cd793fe5e7a7d640bba50aa71ff3f55fe03e49f4
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