James Briggs
Easy natural language generation with Transformers and PyTorch. We apply OpenAI’s GPT-2 model to generate text in just a few lines of Python code.
Language generation is one of those natural language tasks that can really produce an incredible feeling of awe at how far the fields of machine learning and artificial intelligence have come.
GPT-1, 2, and 3 are OpenAI’s top language models — well known for their ability to produce incredibly natural, coherent, and genuinely interesting language.
In this article, we will take a small snippet of text and learn how to feed that into a pre-trained GPT-2 model using PyTorch and Transformers to produce high-quality language generation in just eight lines of code. We cover:
PyTorch and Transformers
– Data
Building the Model
– Initialization
– Tokenization
– Generation
– Decoding
Results
Medium Article:
https://towardsdatascience.com/text-generation-with-python-and-gpt-2-1fecbff1635b
Friend Link (free access):
https://towardsdatascience.com/text-generation-with-python-and-gpt-2-1fecbff1635b?sk=930367d835f15abb4ef3164f7791e1b1
Thumbnail background by gustavo centurion on Unsplash
https://unsplash.com/photos/O6fs4ablxw8