This is not only an implementation of a mini-language model, but also an introductory tutorial for LLMs, aimed at lowering the barrier to learning and getting started with LLMs. It provides the full process code and tutorials from data preprocessing to model training, fine-tuning, and inference. The smallest model has a parameter count of only 0.02B, which can be easily run on a regular GPU.