Transformers are a type of neural network architecture used for natural language processing tasks, including language generation. This article discusses the different decoding methods that can be used with Transformers to generate text. These methods include greedy search, beam search, and sampling-based methods. The article explains how each method works and provides code examples in Python using the Hugging Face library. --- Why it matters: Understanding these decoding methods is important for AI researchers and engineers who work on language generation tasks, as it can impact the quality and coherence of generated text. Source: https://huggingface.co/blog/how-to-generate