Introduction

Education has not been an exception to the many industries where AI breakthroughs have completely changed. Leading this transition and providing unmatched chances to improve learning experiences are open-source large language models (LLMs). Constructed on neural networks, these models are priceless resources for customized education since they can process and produce language that sounds human.

Justifying Open-Source LLMs

Education institutions can easily modify and customize an open-source LLM. In contrast to proprietary closed-source LLMs, open-source models let schools modify them to meet particular requirements without having to pay exorbitant license costs. Innovative educational uses of this flexibility may democratize access to cutting-edge AI technologies.

Principal Educational Use Cases

Educational applications for open-source LLMs are many:

• Customized Content and Feedback: LLMs can adjust to different learning styles and tempos.

Research Assistance: LLMs can swiftly locate pertinent research materials for students and teachers by processing enormous volumes of data.

Automation of Grading: These models guarantee consistency and spare teachers time by quickly grading work and offering rapid feedback.

Popular Education Open-Source LLMs List

The applications of several well-known open-source LLMs in education are summarized here:

1. GPT-NeoX-20B : Developer: EleutherAI : Parameters: 20 billion : Educational Use: Suitable for producing complicated material and research support.

• Complexity: High; calls for specialised technical knowledge.

1. GPT-J-6b : EleutherAI is the developer.6 billion parameters. Educational Use: Suitable for medium-to-high-level educational material creation.

• Complexity: Moderate, made easier to integrate by a helpful neighborhood.

1. Llama 2 – Meta Developer – 7, 13 & 70 billion Parameters

Great for creating teaching resources and educational research.

• Complexity: Simple, however some customisation could be necessary.

BERT – Google is the developer.instructional Use: **Great for enhancing content production and SEO of instructional materials.

For those conversant with SEO techniques, Complexity: Simple.

1. CodeGen – Salesforce Developer; 7 billion, 13 billion, and 34 billion parameters; educational use; appropriate for creating code courses.

The complexity calls for thorough understanding of software engineering.

Standards for Selecting LLMs in Education

Give these things some thought while choosing an LLM for instructional purposes:

Assess hosting and training costs.

• Accuracy: Evaluate how well the model can provide exact instructional material.

Check linguistic coherence and fluency for Performance.

Handling student data requires Data Security.

Conclusion

Selecting the appropriate LLM can revolutionize educational experiences. To fully utilize possible models, carefully assess them according to their capabilities and fit for your particular educational requirements.