Instructions to use AmineAllo/table-transformer-azure-dust-65 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AmineAllo/table-transformer-azure-dust-65 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="AmineAllo/table-transformer-azure-dust-65")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("AmineAllo/table-transformer-azure-dust-65") model = AutoModelForObjectDetection.from_pretrained("AmineAllo/table-transformer-azure-dust-65", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from AmineAllo/table-transformer-azure-dust-65: direct link, hf CLI and curl.
- Browser
- Download file 4.03 kB
-
https://huggingface.co/AmineAllo/table-transformer-azure-dust-65/resolve/main/training_args.bin
- Command line
-
hf download hf://AmineAllo/table-transformer-azure-dust-65/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/AmineAllo/table-transformer-azure-dust-65/resolve/main/training_args.bin
4.03 kB
- Xet hash:
- ecd79be374be19bc6102c8a7373637831597e91e909474e32dabed4a80ad996e
- Size of remote file:
- 4.03 kB
- SHA256:
- a653907150a1338a9451c56a04003e2228010bc60f7a39da92159ef60ef7bf8d
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