Multi-lingual language model Fine-Tuning

Year: 2,019
Journal: EMNLP-IJCNLP / Conference on Empirical Methods in Natural Language Processing and the International Joint Conference on Natural Language Processing
Languages: All Languages
Programming languages: Python
Input data:


We propose Multi-lingual language model Fine-Tuning (MultiFiT) to enable practitioners to train and fine-tune language models efficiently in their own language.

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