Instructions to use binery/table_detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use binery/table_detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="binery/table_detection")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("binery/table_detection") model = AutoModelForObjectDetection.from_pretrained("binery/table_detection") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cc03d7d41ebde8118f998c5d792cf569156213a9db4b11f309704564701e5c8e
- Size of remote file:
- 167 MB
- SHA256:
- 3be55b8629ba12c2ee5653a54fd7492593c2198dc5fb38198312c47ebd228f6e
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