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README.md
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# How to use AraT5 models
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[](https://colab.research.google.com/drive/1GFOGolWPIfDvYdSNdGFrOXwu3Gu28k2b?usp=sharing)This is an example for fine-tuning **AraT5-base** for News Title Generation on the Aranews dataset
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For more details, please visit our own [GitHub](https://github.com/UBC-NLP/araT5).
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In addition, we release the fine-tuned checkpoint of the News Title Generation (NGT) which is described in the paper. The model available at Huggingface ([UBC-NLP/AraT5-base-title-generation](https://huggingface.co/UBC-NLP/AraT5-base-title-generation)).
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# How to use AraT5 models
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[](https://colab.research.google.com/drive/1GFOGolWPIfDvYdSNdGFrOXwu3Gu28k2b?usp=sharing)This is an example for fine-tuning **AraT5-base** for News Title Generation on the Aranews dataset
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In addition, we release the fine-tuned checkpoint of the News Title Generation (NGT) which is described in the paper. The model available at Huggingface ([UBC-NLP/AraT5-base-title-generation](https://huggingface.co/UBC-NLP/AraT5-base-title-generation)).
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For more details, please visit our own [GitHub](https://github.com/UBC-NLP/araT5).
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