Instructions to use peter881122/MyPetModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use peter881122/MyPetModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="peter881122/MyPetModel") 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/MyPetModel") model = AutoModelForImageClassification.from_pretrained("peter881122/MyPetModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from peter881122/MyPetModel: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/peter881122/MyPetModel/resolve/main/training_args.bin
- Command line
-
hf download hf://peter881122/MyPetModel/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/peter881122/MyPetModel/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- 1d803bc933c8e99fe80ed5fb878aa85b90266c2e4ee55a829b9546ef51d417c2
- Size of remote file:
- 5.11 kB
- SHA256:
- b98f618559a9954314122efe7e63d0b71bab866d75d833d433b5ff2fd6788ffe
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