EFFICIENT GENERATION OF SPECIALIZED LARGE LANGUAGE MODELS FOR NETWORK TRAFFIC ANALYSIS
개요
발명자
Lukasz Tulczyjew; Nathanael Weill; Charles Abondo; Albert Khoury Aouad
IPC 분류
CPC 분류
Embodiments relate to generating specialized large language models by performing transfer learning on a base large language model. The base large language model is trained using network traffic capture files as training data to predict information in a network traffic capture file during inference. The base large language model is modified into specialized large language models for including in different applications for performing communication network analysis. In this way, the specialized large language models may be developed in an expedient and efficient manner by leveraging the training performed on the base large language model.
원문 (중국어)
Embodiments relate to generating specialized large language models by performing transfer learning on a base large language model. The base large language model is trained using network traffic capture files as training data to predict information in a network traffic capture file during inference. The base large language model is modified into specialized large language models for including in different applications for performing communication network analysis. In this way, the specialized large language models may be developed in an expedient and efficient manner by leveraging the training performed on the base large language model.