Instructions to use swapnilpote/table-transformer-structure-recognition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use swapnilpote/table-transformer-structure-recognition with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="swapnilpote/table-transformer-structure-recognition")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("swapnilpote/table-transformer-structure-recognition") model = AutoModelForObjectDetection.from_pretrained("swapnilpote/table-transformer-structure-recognition") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2dda54f6b21c7b9a04566f365aee628e0319dde349eade9dfa2aa3e183d41c2e
- Size of remote file:
- 116 MB
- SHA256:
- 43376e04e3037e383ab098ef95cfc9ce61c04f6fecc52c9da927717fd352acdf
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