Instructions to use jabo/deit-base-page-filter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jabo/deit-base-page-filter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="jabo/deit-base-page-filter") 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("jabo/deit-base-page-filter") model = AutoModelForImageClassification.from_pretrained("jabo/deit-base-page-filter") - Notebooks
- Google Colab
- Kaggle
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Page Filtering
Model to identify pages in children's books of the long 19th century (ca. 1789-1914) that contain illustrations. It is used to filter non-relevant pages without illustrations trained on hand-coded data.
Results on our validation dataset:
| f1score | precision | recall | accuracy | |
|---|---|---|---|---|
| not-relevant | 99.63 | 100 | 99.26 | - |
| relevant-cover | 85.71 | 75 | 100 | - |
| relevant-page | 100 | 100 | 100 | - |
| Macro Avg. | 95.11 | 91.67 | 99.75 | 99.37 |
Dataset:
| data | train | test | |
|---|---|---|---|
| not-relevant | 902 | 631 | 271 |
| relevant-cover | 20 | 14 | 6 |
| relevant-page | 136 | 95 | 41 |
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