Instructions to use microsoft/table-transformer-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/table-transformer-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="microsoft/table-transformer-detection")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("microsoft/table-transformer-detection") model = AutoModelForObjectDetection.from_pretrained("microsoft/table-transformer-detection") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 31b886266e51016eacb81e7f1776610082d7f6ecd79505e221f3b548b4d1c119
- Size of remote file:
- 115 MB
- SHA256:
- 8f1aa73170102c038d40155e2734b343bf07e0fe12594228a8590943b01dccf7
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