A tutorial has been released outlining a step-by-step process for creating compact, reasoning-focused language models. The guide involves streaming a dataset from Hugging Face, applying quality filters, and curating data for fine-tuning. It demonstrates an end-to-end pipeline for training and inference, enabling the development of small models with minimal resource requirements. This approach can be useful for organizations looking to create specialized language models without the need for significant computational resources.