ORANSight Qwen-32B Instruct: An O-RAN Expert Assistant

This model is the inaugural release in the ORANSight family, developed by NextG lab@ NC State. It is an instruction-tuned language model built to function as an expert assistant in the domain of Open Radio Access Networks (O-RAN).

Key Capabilities

• Specialized Knowledge: Designed to answer questions and provide explanations related to O-RAN concepts, such as the E2 interface.
• Long-Context Support: Capable of processing inputs up to 128K tokens, allowing for detailed and extensive O-RAN related queries.
• Generative Capacity: Can generate responses up to 8K tokens, suitable for comprehensive explanations and analyses.
• Efficient Fine-Tuning: Leverages the Unsloth framework for fine-tuning, indicating potential optimizations in training and inference.

Good For

• Developers and researchers working with O-RAN technologies who need a specialized AI assistant.
• Educational purposes to explain complex O-RAN interfaces and concepts.
• Applications requiring detailed, context-aware responses within the Open Radio Access Networks domain.

Further details on the model's experiments and results will be available in an upcoming paper. Users are encouraged to cite the foundational work on "Oran-bench-13k" if utilizing this model.