Ziyue-o1 - NetEase Youdao launches China's first reasoning model with step-by-step explanation output.
Ziyue-o1 is the first inference model in China released by NetEase Youdao that outputs step-by-step explanations. The model uses a 14B lightweight architecture, designed specifically for consumer-grade graphics cards, and can run stably on devices with low video memory. Through thought chain technology, it simulates...
What is Confucianism-o1?
Ziyue-o1 is the first reasoning model in China released by NetEase Youdao that provides step-by-step explanations. The model uses a lightweight 14B architecture, designed specifically for consumer-grade graphics cards, and can run stably on devices with low video memory. Through thought chain technology, it simulates human thinking, outputting detailed problem-solving steps in a "self-talking" and self-correcting manner. This step-by-step explanation function is particularly suitable for educational scenarios, helping students better understand and master knowledge. Ziyue-o1 has performed exceptionally well in the education field, especially in K-12 mathematics teaching, providing accurate analytical approaches and answers. The model has been applied to NetEase Youdao's AI all-subject learning assistant, "Youdao Xiao P," supporting a Q&A process that "provides analytical approaches first, then provides answers."
The main functions of Ziyue-o1
- Step-by-step explanationUsing mind chain technology, it can output detailed problem-solving processes in a "self-talking" and self-correcting manner, helping users better understand and master knowledge.
- Lightweight designAs a lightweight single-model with 14B parameters, it is designed for consumer-grade graphics cards and can run stably on devices with low video memory.
- Strong logical reasoningPossesses strong logical reasoning ability, can provide highly accurate problem-solving ideas and answers, and excels especially in mathematical reasoning.
- Educational scenario optimizationBased on in-depth optimization of data in the education field, a large number of student test papers and exercises are used as training samples to improve the application effect in education scenarios.
- Heuristic learningIt supports a Q&A process that "provides the analytical approach first, then the answer," guiding students to think proactively and enhancing their self-learning abilities.
The technical principle of Ziyue-o1
- Mind Chain TechnologyThe Ziyue-o1 model employs thought chain technology, simulating human thinking to form longer thought chains and achieve a reasoning process closer to that of humans. The model "talks to itself" and self-corrects while solving problems, ultimately outputting a step-by-step solution.
- Lightweight designThe model uses a 14-bit parameter scale and is designed specifically for consumer-grade graphics cards, enabling stable operation on devices with low video memory. This lightweight design lowers the hardware barrier, allowing the model to run efficiently on ordinary consumer-grade graphics cards.
- Step-by-step explanation functionAs the first reasoning model in China to provide step-by-step explanations, Ziyue-o1 breaks down complex problem-solving processes into multiple steps, helping users to understand them gradually.
- Self-correction and diversified thinkingThe model has the ability to self-correct during the reasoning process, which can correct erroneous reasoning in a timely manner and explore multiple problem-solving approaches to ensure the accuracy of the final answer.
The project address of 子曰-o1
- HuggingFace model library:https://huggingface.co/netease-youdao/Confucius-o1-14B
- Experience the demo online:https://confucius-o1-demo.youdao.com/
Application scenarios of Ziyue-o1
- K-12 Mathematics TeachingSuitable for student tutoring, family education, and teacher lesson preparation.
- Educational AI AssistantAs an AI tutor, it provides accurate mathematical problem analysis and derivation to improve learning efficiency.
- Intelligent question answering systemIt supports step-by-step reasoning for complex problems and is suitable for intelligent question-answering scenarios that require in-depth analysis.