How to train a new language model from scratch using Transformers and Tokenizers

This article from Hugging Face likely provides a practical guide to building a language model. It focuses on the core components: Transformers, which are the architectural backbone of modern language models, and Tokenizers, which convert text into numerical representations that the model can understand. The article probably covers the steps involved, from data preparation and model architecture selection to training and evaluation. It's a valuable resource for anyone looking to understand the process of creating their own language models, offering insights into the technical aspects of NLP.