Transformers
PyTorch
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/AraT5v2-base-1024 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UBC-NLP/AraT5v2-base-1024 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("UBC-NLP/AraT5v2-base-1024", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 94cec665c55444e5288af065dbd61cf471dd66687c5de34378359aceb5506e7f
- Size of remote file:
- 1.47 GB
- SHA256:
- ff8d294fb609b9dc96a33f3fbc1503936b8921ddf59cced79cebd24fa67de0ce
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