Instructions to use Christian710/table_detection_detr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Christian710/table_detection_detr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="Christian710/table_detection_detr")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("Christian710/table_detection_detr") model = AutoModelForObjectDetection.from_pretrained("Christian710/table_detection_detr") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 61a49ef204e7812e691c0558b2200649d6b3b962bb718d9a64f4ae47c3afa8f5
- Size of remote file:
- 115 MB
- SHA256:
- e4c82d4e96e05316b69ab99d922dc6726643876048419f370946a39278a0b630
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