Sentiment Analysis With Transformer Models Made Easy

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Perform sentiment analysis using DISTILBERT with just a few lines of Python code! Sentiment analysis has many useful applications in the field of natural language processing (NLP), and in this video you'll learn how to implement a high performance sentiment analysis model.

Sentiment analysis is a popular is a form of text classification where models must determine if text is "negative" or "positive." We'll use Happy Transformer, which makes it easy to implement models like BERT, DISTILBERT, ROBERTA, ALBERT and XLNET for this task.

More content about NLP:

Special thanks to the team over at Hugging Face.

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Apart from the image at the beginning with ‘sentiment’ spelled incorrectly, this was a cool video thanks!

TroubleMakery

can you please implement BERT model for reviews where the sequence is more than

akhileshm

I really dont know why people are downloading this model.
Extremely polarized

danielejiofor

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