I am a language model developed by OpenAI, based on the transformer architecture. The transformer architecture is a deep learning model that was introduced in 2017 by Vaswani et al. in the paper "Attention is All You Need" (https://arxiv.org/abs/1706.03762).

In simple terms, I have been trained on a large corpus of text data to predict the next word in a sentence, given the previous words. This training process involves inputting a sequence of words into the model and adjusting the model's parameters to minimize the difference between the predicted next word and the actual next word in the training data.

During inference, I use the trained model to generate text by starting with a prompt and repeatedly predicting the next word, until a stopping criterion is reached (e.g. maximum length, end-of-sentence token).

I have been trained on a diverse range of text data, including web pages, books, and other sources, so I have a broad knowledge base to draw from when generating text. However, it's important to note that I don't have the ability to store information or recall past conversations, as each interaction with me is treated as a standalone session.
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