ERC-ITEA/MuduoLLM

Hugging Face
TEXT GENERATIONConcurrency Cost:1Model Size:14.8BQuant:FP8Ctx Length:32kPublished:May 27, 2025License:apache-2.0Architecture:Transformer0.0K Open Weights Warm

MuduoLLM is a 14.8 billion parameter foundational educational large language model developed by Beijing Normal University and TAL Education Group, based on the Qwen2.5-14B-Instruct architecture. It is specifically aligned with China's new curriculum standards, ensuring high fidelity to educational content. This model excels in knowledge-based intelligent problem-solving, inquiry-guided Q&A, context-driven question generation, and competency-oriented lesson planning, making it ideal for educational applications focused on core competency cultivation.

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MuduoLLM: A Specialized Educational LLM

MuduoLLM is the first foundational educational large language model developed jointly by Beijing Normal University and TAL Education Group. It is built upon the Qwen2.5-14B-Instruct base architecture, featuring 14.8 billion parameters, and is uniquely aligned with China's new curriculum standards to support basic education.

Key Capabilities & Features

  • Curriculum Alignment: Ensures high fidelity to educational content and precisely addresses student core competency cultivation and teacher professional growth.
  • Educational AI Functions: Deeply integrates new curriculum knowledge and pedagogy to offer:
    • Knowledge-based intelligent problem-solving.
    • Inquiry-guided intelligent Q&A.
    • Context-driven intelligent question generation.
    • Competency-oriented lesson plan generation.
  • Training Methodology: Enhanced through a multi-stage training process:
    • Domain-specific Pretraining: Injected educational corpora to improve semantic understanding.
    • Supervised Fine-Tuning (SFT): Optimized for specific educational scenarios like question generation, Q&A, and lesson plan creation.
    • Direct Preference Optimization (DPO): Utilized expert-annotated preference data to improve generation accuracy and adherence to educational ethics.
  • Performance: Positioned as one of the most capable open-source foundational models in basic education, offering significant potential for further optimization.

Ideal Use Cases

  • Developing AI tutors or educational assistants.
  • Automating content generation for educational materials.
  • Creating intelligent assessment tools.
  • Supporting teacher professional development through AI-generated lesson plans and teaching aids.

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