Transformers
PyTorch
TensorFlow
Arabic
t5
text2text-generation
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-base-title-generation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UBC-NLP/AraT5-base-title-generation with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("UBC-NLP/AraT5-base-title-generation") model = AutoModelForSeq2SeqLM.from_pretrained("UBC-NLP/AraT5-base-title-generation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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