Since its reveal in 2017 in the popular paper Attention Is All You Need (https://arxiv.org/abs/1706.03762), the Transformer quickly became the most popular model in NLP. The ability to process text in a non-sequential way (as opposed to RNNs) allowed for training of big models. The attention mechanism it introduced proved extremely useful in generalizing text.
Following the paper, several popular transformers surfaced, the most popular of which is GPT. GPT models are developed and trained by OpenAI, one of the leaders in AI research. The latest release of GPT is GPT-3, which has 175 billion parameters. The model was very advanced to the point where OpenAI chose not to open-source it. People can access it through an API after a signup process and a long queue.
However, GPT-2, their previous release is open-source and available on many deep learning frameworks.
In this excercise, we use Huggingface and PyTorch to fine-tune a GPT-2 model
from Planet SciPy
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