asafaya/bert-large-arabic

The model was trained using Google BERT's GitHub repository on a single TPU v3-8 provided for free from TFRC . It was trained for 3M training steps with batchsize of 128, instead of 1M with batch size of 256 . The final version of corpus contains some non-Arabic words inlines, which we did not remove from sentences since that would affect some tasks like NER . There is no cased and uncased version of the model, since Arabic characters does not have upper or lower case, there is no case and uncase versions . You can use this model by installing torch or tensorflow and Huggingface library transformers. And you can,