Instructions to use peter881122/swinModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use peter881122/swinModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="peter881122/swinModel") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("peter881122/swinModel") model = AutoModelForImageClassification.from_pretrained("peter881122/swinModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from peter881122/swinModel: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/peter881122/swinModel/resolve/main/training_args.bin
- Command line
-
hf download hf://peter881122/swinModel/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/peter881122/swinModel/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- ed57684eba45869c27dc3a2098476db17f3a246a1ee15efd6ffa4da86e9d5526
- Size of remote file:
- 5.11 kB
- SHA256:
- e7543b677e4d5a0b6270b05f4f95b4fca0c45495641c19f4fe60497da8b90eae
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