Instructions to use crapthings/vit-base-beans with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use crapthings/vit-base-beans with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="crapthings/vit-base-beans") 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("crapthings/vit-base-beans") model = AutoModelForImageClassification.from_pretrained("crapthings/vit-base-beans", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b1f3e6938354879e2ae2a989d614affeb8f2427fc71631fd72cd8d72b7a577c0
- Size of remote file:
- 5.24 kB
- SHA256:
- ecd414c5caee1ff28e6882e4ca6b918622b0b82b04dfa7d1dda8e90ec82bf23e
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