Instructions to use binery/Table_Detection_MS_E_37 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use binery/Table_Detection_MS_E_37 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="binery/Table_Detection_MS_E_37")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("binery/Table_Detection_MS_E_37") model = AutoModelForObjectDetection.from_pretrained("binery/Table_Detection_MS_E_37") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c1b23d0ce67e328348d8ee54b98d90e076f928671ad890d05d786e71913ac3db
- Size of remote file:
- 115 MB
- SHA256:
- 9dc4e397f917160335055be78164d2b968ba01d54a64341ec522c1b7582bd755
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