Instructions to use SalML/DETR-table-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SalML/DETR-table-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="SalML/DETR-table-detection")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("SalML/DETR-table-detection") model = AutoModelForObjectDetection.from_pretrained("SalML/DETR-table-detection") - Notebooks
- Google Colab
- Kaggle
The models are taken from https://github.com/microsoft/table-transformer/
Original model now on MSFT org: https://huggingface.co/microsoft/table-transformer-detection
I have built a HuggingFace Space: https://huggingface.co/spaces/SalML/TableTransformer2CSV It runs an OCR on the table-transformer output image to obtain a CSV downloadable table.
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