Instructions to use sg485/Resnet34_Table_Transformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sg485/Resnet34_Table_Transformer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="sg485/Resnet34_Table_Transformer")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("sg485/Resnet34_Table_Transformer") model = AutoModelForObjectDetection.from_pretrained("sg485/Resnet34_Table_Transformer") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4031f0c45b868aea01568d49005cd4b924552a9b858f2b07a40c89826e5b2759
- Size of remote file:
- 156 MB
- SHA256:
- 0889e75119ff099910c3f3295d6a446f4671e9c9418c99fbb406dc6a0067e5a4
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