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What it does do pretty well is construct grammatically correct sentences from fragments. Transformers can be difficult to train, but luckily for us, we've got HuggingFace, a library that provides an easy interface to access pre-trained transformers.I am going to take a full year to cover the 6 areas of deep learning (I'll mention which ones a bit later) that are super interesting to me. In this tutorial, we will discuss one of the most impactful architectures of the last 2 years: the Transformer model. We trained a GPT2 model on Harry Potter books. The trained model is able to generate text like Harry Potter books when presented with an input. I want to do the prediction of only next word with the probabilities. The aim of this tutorial is to provide a comprehensive understanding of how to construct a Transformer model using PyTorch. Learn how to use a custom LLM transformer in Neosync in order to call an LLM on every row to generate data or anonymize existing data. Is there a list of models in HF transformers that support FIM?