Instructions to use simlaharma/vit-base-beans with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use simlaharma/vit-base-beans with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="simlaharma/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("simlaharma/vit-base-beans") model = AutoModelForImageClassification.from_pretrained("simlaharma/vit-base-beans", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from simlaharma/vit-base-beans: direct link, hf CLI and curl.
- Browser
- Download file 3.52 kB
-
https://huggingface.co/simlaharma/vit-base-beans/resolve/refs%2Fpr%2F2/training_args.bin
- Command line
-
hf download hf://simlaharma/vit-base-beans@refs/pr/2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/simlaharma/vit-base-beans/resolve/refs%2Fpr%2F2/training_args.bin
3.52 kB
- Xet hash:
- c3e55b84073bf6d5132daaa4af47aa22a8f28ecd29908092021a63ccaaa3bce3
- Size of remote file:
- 3.52 kB
- SHA256:
- 666ed5387f2ada8cddc048307806f19023db9781cf8f97162c63c38bf8c05241
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