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", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7b0b1da8dc8a0bbf2b1f607d842b6077398a337b4db06139bcbe5414a2987721
- Size of remote file:
- 2.35 MB
- SHA256:
- 180428eb8e88be6c7d259fb04c9eb3a1c552d799a76741bcd6ee34fa0bf64386
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.