Instructions to use roshan151/table_detection_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use roshan151/table_detection_v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="roshan151/table_detection_v1")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("roshan151/table_detection_v1") model = AutoModelForObjectDetection.from_pretrained("roshan151/table_detection_v1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- df16b6d8cf5cf4dd605094b2e6cb9690378dd238d66a925694b26a96cf3c44a0
- Size of remote file:
- 115 MB
- SHA256:
- 31919a000dcce55c4aaf7841b2af73d76e5b5c65aea6e9c0f020f86e46ebdef1
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