Instructions to use gmnj/table_detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gmnj/table_detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="gmnj/table_detection")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("gmnj/table_detection") model = AutoModelForObjectDetection.from_pretrained("gmnj/table_detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download Fine_Tuning_DetrObjectDetection_model.pth from gmnj/table_detection: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/gmnj/table_detection/resolve/refs%2Fpr%2F1/Fine_Tuning_DetrObjectDetection_model.pth
- Command line
-
hf download hf://gmnj/table_detection@refs/pr/1/Fine_Tuning_DetrObjectDetection_model.pth
-
curl -L -o Fine_Tuning_DetrObjectDetection_model.pth https://huggingface.co/gmnj/table_detection/resolve/refs%2Fpr%2F1/Fine_Tuning_DetrObjectDetection_model.pth
167 MB
- Xet hash:
- 271966bc61ad130015243f00b30dba13d278433b187f2dc57b0e5b1d574694ec
- Size of remote file:
- 167 MB
- SHA256:
- eb6f656dfc319ac726939358713a8b5622a12183d9c4d92a24246732196b26cd
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