Transformers
PyTorch
TensorFlow
Arabic
t5
Arabic T5
MSA
Twitter
Arabic Dialect
Arabic Machine Translation
Arabic Text Summarization
Arabic News Title and Question Generation
Arabic Paraphrasing and Transliteration
Arabic Code-Switched Translation
text-generation-inference
Instructions to use UBC-NLP/AraT5-msa-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UBC-NLP/AraT5-msa-base with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("UBC-NLP/AraT5-msa-base", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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# AraT5-msa-base
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# AraT5: Text-to-Text Transformers for Arabic Language Generation
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---
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language:
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- ar
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tags:
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- Arabic T5
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- MSA
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- Twitter
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- Arabic Dialect
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- Arabic Machine Translation
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- Arabic Text Summarization
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- Arabic News Title and Question Generation
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- Arabic Paraphrasing and Transliteration
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- Arabic Code-Switched Translation
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---
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# AraT5-msa-base
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# AraT5: Text-to-Text Transformers for Arabic Language Generation
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