Instructions to use mmekias/vit-base-beans with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mmekias/vit-base-beans with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="mmekias/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("mmekias/vit-base-beans") model = AutoModelForImageClassification.from_pretrained("mmekias/vit-base-beans", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d6e60c6c0063f58426942a54e5f4c9a2a83fbaad61c09e97efa7ef2436df99bf
- Size of remote file:
- 2.86 kB
- SHA256:
- 6087521fe76b206063b7b68ad1643354cc033f444cbe2eabfb02b614653db039
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