4小时喜提专属 ChatGPT、卡帕西又整活！自曝Agent帮倒忙、手搓八千行代码，网友：跑完就当上机器学习工程师

Core Insights - The article discusses the launch of "nanochat," an open-source project by Andrej Karpathy, which allows users to train a simplified version of ChatGPT with minimal resources [2][4][6] - Karpathy claims that with just $100 and approximately 4 hours of training on a cloud GPU server, users can create a conversational model that surpasses GPT-2 in performance [6][7] Project Overview - "nanochat" is a streamlined training and inference toolchain built from scratch, differing from Karpathy's previous project, "nanoGPT," which only included pre-training functionalities [2][5] - The entire codebase consists of around 8000 lines of code, emphasizing clarity and simplicity, making it suitable for modification and branch development [11][12] Technical Specifications - The project utilizes a new tokenizer implemented in Rust and pre-trains a Transformer-based language model on the FineWeb dataset [5] - Key features include instruction fine-tuning, reinforcement learning options, and an efficient inference engine with a user-friendly interface [6][9] Performance Metrics - After approximately 12 hours of training, the model's performance metrics exceed those of GPT-2, with specific scores on various benchmarks such as MMLU and GSM8K [7][8] - The CORE score for the model after different training stages is provided, showing improvements across various metrics [8] Community and Future Development - Karpathy envisions "nanochat" as a core project for an upcoming course and a potential research tool framework, inviting community contributions for further enhancements [9][14] - The project has generated significant interest on social media, with users expressing excitement about its potential for machine learning education and experimentation [14]