Gretel Tweets

In this blog post, we explore fine-tuning a multi-billion parameter large language model (LLM) using Gretel GPT to answer questions as if it were any of your favorite Twitter personalities. We walk through the steps of training the model with recent tweets from popular Twitter users and provide examples of how the adapted model can be used to generate text reflecting each personality's tone and style. The project is inspired by Boris Dayma's HuggingTweets, which uses a similar approach for generating synthetic tweets. We demonstrate how to compile a list of Twitter users, preprocess their tweets, create a training set, configure the Gretel training process, initiate model training, and generate queries using the trained model. Finally, we examine the results and discuss potential improvements and future directions for this experiment.