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Top 3 Fine-Tuned T5 Transformer Models (Text-to-Text NLP)
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Learn how to implement my top 3 favourite T5 models that are available on Hugging Face's Model Hub. T5 is a state-of-the-art natural langauge processing (NLP) Transformer model that you can use with just a few lines of Python code.
The three models covered in this video include a paraphrasing model, a keyword to text model and finally a grammar correction model. All of these models are text-to-text T5 models.
My very own Happy Transformer NLP library is used for this tutorial. Happy Transformer is built on top of Hugging Face's Transformers library and makes it easy to implement and train Transformer models with just a few lines of code.
Learn how to upload a model to Hugging Face’s Model Hub:
Please give Happy Transformer a star to help support it:
0:00 - Introduction
0:49 - Overview of models
1:00 - Full article
1:14 - Happy Transformer
1:41 - Paraphrasing model
3:44 - GPT-Neo course
4:30 - Keywords to text model
5:36 - Grammar correction model
6:36 - Conclusion
The three models covered in this video include a paraphrasing model, a keyword to text model and finally a grammar correction model. All of these models are text-to-text T5 models.
My very own Happy Transformer NLP library is used for this tutorial. Happy Transformer is built on top of Hugging Face's Transformers library and makes it easy to implement and train Transformer models with just a few lines of code.
Learn how to upload a model to Hugging Face’s Model Hub:
Please give Happy Transformer a star to help support it:
0:00 - Introduction
0:49 - Overview of models
1:00 - Full article
1:14 - Happy Transformer
1:41 - Paraphrasing model
3:44 - GPT-Neo course
4:30 - Keywords to text model
5:36 - Grammar correction model
6:36 - Conclusion
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