Instructions to use bookworm88/vit224-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bookworm88/vit224-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="bookworm88/vit224-2") 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("bookworm88/vit224-2") model = AutoModelForImageClassification.from_pretrained("bookworm88/vit224-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Check out the documentation for more information.
Usage:
Image classification
Project:
Cover quilt
Labels:
11covered_with_a_quilt_and_only_the_head_exposed
12covered_with_a_quilt_and_exposed_other_parts_of_the_body
Indicators:
Accuracy: 0.9591836734693877
Precision: 0.9545454545454546
Recall: 0.9655172413793103
F1 Score: 0.9583333333333333
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