Instructions to use afford6522/vit-beans-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use afford6522/vit-beans-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="afford6522/vit-beans-classifier") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("afford6522/vit-beans-classifier") model = AutoModelForImageClassification.from_pretrained("afford6522/vit-beans-classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2aefdbdd5161df2d6b98a91c55984e923f013a2761b091fb1c5f8ca7bc717b2a
- Size of remote file:
- 5.91 kB
- SHA256:
- f23557ee8a259e7dd00a6a33c3d18c38f7d331ab41cf2b6ef38bf9b222905b29
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.