Easy Machine Translation with Machine Learning and HuggingFace Transformers

By MachineCurve - 2021-02-15

Description

Machine Translation with Python and Transformers - learn how to build an easy pipeline for translation and to extend it to more languages.

Summary

Transformers have significantly changed the way in which Natural Language Processing tasks can be performed.
pipelines for Machine Translation The two code examples below give fully working examples of pipelines for Machine Translation.
Using a Common Crawl-derived dataset called C4 and by prefixing the various tasks with instructions (such as “translate” or “summarize”), the authors were able to create a model that can be used for a variety of language tasks when finetuned for these tasks.
We also showed you how to create a pipeline for any pretrained Seq2Seq model for translation available within HuggingFace, using an English-to-Dutch translation model as an example.

Topics

NLP (0.4)
Machine_Learning (0.25)
Backend (0.13)

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