scgsai/NetworkExpert

Hugging Face
TEXT GENERATIONConcurrency Cost:1Model Size:4BQuant:BF16Ctx Length:32kPublished:Mar 4, 2026License:apache-2.0Architecture:Transformer Open Weights Warm

NetworkExpert is a 4 billion parameter domain-specific large language model developed by 广州数创共生人工智能技术有限公司, fine-tuned from Qwen2.5-7B-Instruct. Optimized for enterprise network operations and fault diagnosis, it excels at tasks like configuration parsing, troubleshooting, command generation, and knowledge Q&A for Cisco, Huawei, and H3C devices. This model is specifically designed to enhance network maintenance automation and intelligent diagnosis platforms.

Loading preview...

NetworkExpert: Domain-Specific LLM for Network Operations

NetworkExpert is a specialized large language model (LLM) developed by 广州数创共生人工智能技术有限公司, fine-tuned from Qwen2.5-7B-Instruct. It is specifically designed for enterprise network operations and fault diagnosis, leveraging training on hundreds of thousands of network configurations, fault cases, and technical documents.

Key Capabilities

  • Configuration Parsing: Automatically identifies configurations from mainstream vendors like Cisco, Huawei, and H3C.
  • Fault Diagnosis: Performs root cause analysis and recommends solutions based on logs and observed phenomena.
  • Command Generation: Creates standard configuration commands and scripts based on requirements.
  • Knowledge Q&A: Answers questions on network protocols, architecture design, and best practices.
  • Compliance Checks: Identifies security risks and potential hidden dangers in network configurations.

Good for

  • Automating enterprise network operations.
  • Intelligent network fault diagnosis platforms.
  • Network configuration management and auditing tools.
  • Building network operations knowledge base Q&A systems.

Limitations

Primarily trained on Chinese network technical documents, with limited support for other languages. Model outputs are for reference only; critical configuration changes require professional review. It cannot directly access live network devices and its knowledge may be limited by training data age.