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-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UBC-NLP/AraT5-msa-small with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("UBC-NLP/AraT5-msa-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f3af47b8aea18e081e607f6e0f47491ab63f604d39364763ea57d4bb5a69c683
- Size of remote file:
- 453 MB
- SHA256:
- 61f19ebee2fc95aee0cd468fe77eaf42c2127d794e7a98f9dccc19b33086d3bc
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