MiniMind is an open-source GitHub project that enables users to train a 26M-parameter tiny LLM from scratch in just 2 hours with a cost of 3 RMB. It provides native PyTorch implementations for Tokenizer training, pretraining, supervised fine-tuning (SFT), LoRA, DPO, PPO/GRPO reinforcement learning, and MoE architecture with vision multimodal extensions. It includes high-quality open datasets, supports single-GPU training, and is compatible with Transformers, llama.cpp, and other frameworks, ideal for LLM beginners.
