Reinforcement Learning for tuning language models ( how to train ChatGPT )

The Large Language Model revolution started with the advent of transformers in 2017. Since then there has been an exponential growth in the models trained. Models with 100B+ parameters have been trained. These pre-trained models have changed the way NLP is done. It is much easier to pick a pre-trained model and fine-tune it for a downstream task ( sentiment, question answering, entity recognition etc.. ) than training a model from scratch. Fine-tuning can be done with a much smaller set of examples than training a model from scratch making the whole process of NLP much easier.

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