Instructions to use binery/Table_detection_MS_E_14 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use binery/Table_detection_MS_E_14 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="binery/Table_detection_MS_E_14")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("binery/Table_detection_MS_E_14") model = AutoModelForObjectDetection.from_pretrained("binery/Table_detection_MS_E_14") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0390594fe44da8e0a529aef4bbfb397307548ea7ba2eee4e021e78938db171f0
- Size of remote file:
- 115 MB
- SHA256:
- 32d39f6ae0406bd3a112a475456c9936d65e390d43a8048943d4819efed8a83f
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