Automated Summarisation of PDFs with GPT API in Python
Background
Of course, jump ahead if you have had too much on what GPT can do.
The GPT (Generative Pre-trained Transformer) is a powerful language model developed by OpenAI, which has revolutionised the field of natural language processing (NLP). It is a neural network-based system that has been pre-trained on a massive corpus of text data and is capable of generating high-quality text content, including articles, summaries, and responses to queries.
The GPT API was first released in 2018 and has since undergone several improvements and updates, including the latest version, GPT-3, which was released in June 2020. This version has 175 billion parameters, making it one of the largest and most powerful language models ever created. It has been trained on a diverse range of text sources, including books, articles, and web pages, and has been shown to outperform previous language models on a variety of NLP tasks.
One of the most exciting features of the GPT API is its ability to generate coherent and concise summaries of long texts. This capability has numerous applications, including in the field of document analysis, where it can be used quickly and efficiently to summarise large volumes of text data.
