With the rapid pace of development in machine learning, the quality of seq2seq translation models are fast approaching what's available on cloud platforms. Conv

With the rapid pace of development in machine learning, the quality of seq2seq translation models are fast approaching what's available on cloud platforms. Convenience, cost and privacy are all good reasons to consider. In the case of low-resource languages, cloud translation may not exist. Couple models to highlight (available on the Hugging Face Hub): facebook/mbart-large-50: Supports translating between 50 different languages. https://huggingface.co/facebook/mbart-large-50 https://huggingface.co/facebook/mbart-large-50 facebook/m2m100_418M: Supports translating between 100 different languages. https://huggingface.co/facebook/m2m100_418M https://huggingface.co/facebook/m2m100_418M facebook/nllb-200-distilled-600M: Translations between 200 languages, including low-resource languages. https://huggingface.co/facebook/nllb-200-distilled-600M https://huggingface.co/facebook/nllb-200-distilled-600M