| # MorRoBERTa | |
| MorRoBERTa, designed specifically for the Moroccan Arabic dialect, is a scaled-down variant of the RoBERTa-base model. It comprises 6 layers, 12 attention heads, and 768 hidden dimensions. The training process spanned approximately 92 hours, covering 12 epochs on the complete training set. A vast corpus of six million Moroccan dialect sentences, amounting to 71 billion tokens, was used to train this model. | |
| ## Usage | |
| The model weights can be loaded using transformers library by HuggingFace. | |
| from transformers import AutoTokenizer, AutoModel | |
| tokenizer = AutoTokenizer.from_pretrained("otmangi/MorRoBERTa") | |
| model = AutoModel.from_pretrained("otmangi/MorRoBERTa") | |