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🤯 Did You Know (click to read)
mBERT was trained on Wikipedia text in 104 languages, enabling cross-lingual transfer learning for multiple NLP tasks.
Cross-lingual Transformers like XLM and mBERT are pretrained on multiple languages. Self-attention allows the model to learn shared semantic representations across languages, enabling zero-shot translation and multilingual understanding without task-specific training for each language.
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💥 Impact (click to read)
Cross-lingual Transformers improve global communication, multilingual search, and translation services, supporting international applications.
Researchers and developers can leverage pretrained multilingual Transformers to deploy NLP systems for low-resource languages efficiently.
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