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EXLMR has been designed with specific support for underrepresented languages, particularly those spoken in Ethiopia (such as Amharic, Tigrinya, and Afaan Oromo).Like XLM-RoBERTa, EXLMR can handle multiple languages simultaneously, making it effective for cross-lingual tasks such as machine translation, multilingual text classification, and question answering.EXLMR-base follows the same architecture as RoBERTa-base, with 12 layers, 768 hidden dimensions, and 12 attention heads, totaling approximately 270M parameters. |
