Instructions to use dim/vit-base-beans with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dim/vit-base-beans with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="dim/vit-base-beans") 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("dim/vit-base-beans") model = AutoModelForImageClassification.from_pretrained("dim/vit-base-beans", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from dim/vit-base-beans: direct link, hf CLI and curl.
- Browser
- Download file 5.84 kB
-
https://huggingface.co/dim/vit-base-beans/resolve/main/training_args.bin
- Command line
-
hf download hf://dim/vit-base-beans/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/dim/vit-base-beans/resolve/main/training_args.bin
5.84 kB
- Xet hash:
- d33d8ff70be7019b1ddb614964f5fda53787c162efd67b1ac2223ffcef428600
- Size of remote file:
- 5.84 kB
- SHA256:
- b367d9b8d167a206562d6acc21d8467e57e440733b91b91326973b2604dca502
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