Instructions to use fmagot01/vit-base-beans with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fmagot01/vit-base-beans with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="fmagot01/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("fmagot01/vit-base-beans") model = AutoModelForImageClassification.from_pretrained("fmagot01/vit-base-beans", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aab25e66e1d5a3aa6f901af2a9d14a8162d5aa829d632aa7b37f8b54c1fb76af
- Size of remote file:
- 4.03 kB
- SHA256:
- 8d6547cb2fe53f5474f5d5e537eb562df119a5e8ffebade5343b1c0338e9f2d1
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