Large Model Training Lab
Introduction
Large Model Practical Training Lab is mainly based on large models and search enhancement generation, combined with large-scale corpus, to realize intelligent retrieval and generation of private domain knowledge, so as to improve the efficiency and accuracy of knowledge application. The training lab realizes multi-modal understanding based on pictures and texts uploaded by users, answers users' questions around uploaded materials, and then completes the collection and sorting of knowledge materials and the creation, training and application of knowledge base. The specific implementation contents include LLM, RAG, knowledge base system construction and knowledge base system training, which can support the ability training of artificial intelligence trainers, artificial intelligence application development engineers and other positions.
Applicable major: artificial intelligence/intelligent science and technology/computer related majors
Course product: deep learning, natural language, AI large model foundation and application development, LangChain Foundation and application development
Project product: installation, deployment and measurement of intelligent question answering system, Qwen3B and ChatGLM3-6B models based on big model Web
Application scenario: professional teaching, comprehensive practical training, competition training
Feature
Keep up with hot spots
The project focuses on the design of large model and AIGC, and the practical application of LLM large model +RAG, and the real application scenario of enterprise based on knowledge base Agent.
Large technical coverage
It covers operating system, container, large model, RAG, application software, front-end UI development, docker principle and deployment, vector database, knowledge base application engineering and other technologies, improving students' skills in all aspects and strengthening the ability to combine professional courses with practice.
The technology is new and easy to use
The core technology adopts the latest and mainstream LLM(large language model), RAG(search enhancement generation), Embedding, Vue, SpringBoot, and encapsulation friendly, low coupling, easy for students to get started.
Scene diversification
In addition to helping teachers carry out practical teaching, the system can also provide educational assistance, acting as a teaching assistant to answer students' common questions about courses and practical training around the clock. At the same time, online customer service can automatically answer customer inquiries to improve service efficiency and user satisfaction; In addition, it can also provide psychological counseling to understand and respond to the emotional needs of users.
Large Model Practical Training Lab is mainly based on large models and search enhancement generation, combined with large-scale corpus, to realize intelligent retrieval and generation of private domain knowledge, so as to improve the efficiency and accuracy of knowledge application. The training lab realizes multi-modal understanding based on pictures and texts uploaded by users, answers users' questions around uploaded materials, and then completes the collection and sorting of knowledge materials and the creation, training and application of knowledge base. The specific implementation contents include LLM, RAG, knowledge base system construction and knowledge base system training, which can support the ability training of artificial intelligence trainers, artificial intelligence application development engineers and other positions.
Applicable major: artificial intelligence/intelligent science and technology/computer related majors
Course product: deep learning, natural language, AI large model foundation and application development, LangChain Foundation and application development
Project product: installation, deployment and measurement of intelligent question answering system, Qwen3B and ChatGLM3-6B models based on big model Web
Application scenario: professional teaching, comprehensive practical training, competition training
Feature
Keep up with hot spots
The project focuses on the design of large model and AIGC, and the practical application of LLM large model +RAG, and the real application scenario of enterprise based on knowledge base Agent.
Large technical coverage
It covers operating system, container, large model, RAG, application software, front-end UI development, docker principle and deployment, vector database, knowledge base application engineering and other technologies, improving students' skills in all aspects and strengthening the ability to combine professional courses with practice.
The technology is new and easy to use
The core technology adopts the latest and mainstream LLM(large language model), RAG(search enhancement generation), Embedding, Vue, SpringBoot, and encapsulation friendly, low coupling, easy for students to get started.
Scene diversification
In addition to helping teachers carry out practical teaching, the system can also provide educational assistance, acting as a teaching assistant to answer students' common questions about courses and practical training around the clock. At the same time, online customer service can automatically answer customer inquiries to improve service efficiency and user satisfaction; In addition, it can also provide psychological counseling to understand and respond to the emotional needs of users.
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