Скачать или смотреть Building a Pipeline for State-of-the-Art Natural Language Processing Using Hugging Face Tools

The natural language processing (NLP) landscape has radically changed with the arrival of transformer networks in 2017. From BERT to XLNet, ALBERT and ELECTRA, huge neural networks now manage to obtain unprecedented scores on benchmarks for tasks like sequence classification, question answering and named entity recognition. The pipeline from text to prediction remains complex, but tools like huggingface/transformers and huggingface/tokenizers take most of the burden off of the user, offering a simple API. This talk will focus on the entire NLP pipeline, from text to tokens with huggingface/tokenizers and from tokens to predictions with huggingface/transformers.

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