Instructions to use AmineAllo/table-transformer-true-bush-63 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AmineAllo/table-transformer-true-bush-63 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="AmineAllo/table-transformer-true-bush-63")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("AmineAllo/table-transformer-true-bush-63") model = AutoModelForObjectDetection.from_pretrained("AmineAllo/table-transformer-true-bush-63", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from AmineAllo/table-transformer-true-bush-63: direct link, hf CLI and curl.
- Browser
- Download file 4.03 kB
-
https://huggingface.co/AmineAllo/table-transformer-true-bush-63/resolve/main/training_args.bin
- Command line
-
hf download hf://AmineAllo/table-transformer-true-bush-63/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/AmineAllo/table-transformer-true-bush-63/resolve/main/training_args.bin
4.03 kB
- Xet hash:
- 143a904ee7ee29001755f69dbc63dca1ccc916f7fcf00ba964718d711ad945fc
- Size of remote file:
- 4.03 kB
- SHA256:
- 819c50ee97dd37f7752341df12abe1ab2743952cb96875b8f066e237074b3f55
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