NextGLab/ORANSight_LLama_8B_Instruct
ORANSight_LLama_8B_Instruct is an 8 billion parameter instruction-tuned language model developed by NextG lab@ NC State, specifically fine-tuned for expertise in Open Radio Access Networks (O-RAN). Utilizing the Unsloth framework, this model is designed to function as an O-RAN expert assistant, making it ideal for specialized queries and tasks within the telecommunications domain. It features a context window of 128K tokens, enabling it to process extensive O-RAN related information.
Loading preview...
ORANSight Llama-8B: O-RAN Expert Assistant
ORANSight_LLama_8B_Instruct is the inaugural model in the ORANSight family, developed by NextG lab@ NC State. This 8 billion parameter instruction-tuned model is specifically designed to serve as an O-RAN expert assistant, making it a specialized tool for tasks within Open Radio Access Networks.
Key Capabilities
- Specialized O-RAN Expertise: Fine-tuned to understand and explain complex concepts related to O-RAN, such as the E2 interface.
- Large Context Window: Features a 128K token context window, allowing for processing and understanding of extensive O-RAN documentation and queries.
- Efficient Fine-Tuning: Developed using the Unsloth framework, indicating an optimized approach to fine-tuning.
Good for
- Developers and researchers working on O-RAN related projects.
- Applications requiring detailed explanations and insights into O-RAN architecture and protocols.
- Building chatbots or assistants focused on telecommunications and radio access networks.
This model is licensed under llama3.1. A detailed paper documenting its experiments and results is anticipated soon, building upon foundational work such as "Oran-bench-13k: An open source benchmark for assessing llms in open radio access networks".