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README.md
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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.
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The model weights can be loaded using transformers library by HuggingFace.
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from transformers import AutoTokenizer, AutoModel
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tokenizer = AutoTokenizer.from_pretrained("otmangi/MorRoBERTa")
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model = AutoModel.from_pretrained("otmangi/MorRoBERTa")
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# MorRoBERTa
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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.
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## Usage
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The model weights can be loaded using transformers library by HuggingFace.
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from transformers import AutoTokenizer, AutoModel
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tokenizer = AutoTokenizer.from_pretrained("otmangi/MorRoBERTa")
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model = AutoModel.from_pretrained("otmangi/MorRoBERTa")
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