Instructions to use pphildan/vit-base-patch16-224-v17_4e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pphildan/vit-base-patch16-224-v17_4e with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="pphildan/vit-base-patch16-224-v17_4e") 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("pphildan/vit-base-patch16-224-v17_4e") model = AutoModelForImageClassification.from_pretrained("pphildan/vit-base-patch16-224-v17_4e", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from pphildan/vit-base-patch16-224-v17_4e: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/pphildan/vit-base-patch16-224-v17_4e/resolve/main/training_args.bin
- Command line
-
hf download hf://pphildan/vit-base-patch16-224-v17_4e/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/pphildan/vit-base-patch16-224-v17_4e/resolve/main/training_args.bin
3.96 kB
- Xet hash:
- 56f9cc3d5960e5c2266fe0d7fd956267fe96f6150fa3b1b84d4b92c14ed428ce
- Size of remote file:
- 3.96 kB
- SHA256:
- e798eb604f3b24dbd3173888949b0117b1034e42e4d9a6032ca846ceca87e276
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