Techniques for leveraging edge-deployed generative ai for enhanced asset performance management

A non-transitory computer-readable medium storing a set of instructions, that, when executed by one or more processors of a device, cause the device to perform operations comprising:

• receiving a first input comprising a selected base model from a plurality of base models;
• receiving a second input comprising one or more selected transformer models;
• collecting domain-specific text data;
• curating multi-modal datasets using the one or more selected transformer models;
• labeling the domain-specific text data and the multi-modal datasets using domain-specific metadata;
• modifying the selected base model by freezing one or more large layers of the selected base model and fine-tuning one or more adapter layers of the selected base model;
• training the modified base model using the labeled domain specific text data and the labeled multi-modal datasets using a transfer learning processes;
• training an edge model using the trained, modified base model;
• converting the edge model into executable code;
• and
• storing the executable code in a memory.

A system comprising:

• one or more processors configured to access code stored in a memory to perform operations comprising:
• receiving a first input comprising a selected base model from a plurality of base models;
• receiving a second input comprising one or more selected transformer models;
• collecting domain-specific text data;
• curating multi-modal datasets using the one or more selected transformer models;
• labeling the domain-specific text data and the multi-modal datasets using domain-specific metadata;
• modifying the selected base model by freezing one or more large layers of the selected base model and fine-tuning one or more adapter layers of the selected base model;
• training the modified base model using the labeled domain specific text data and the labeled multi-modal datasets using a transfer learning processes;
• training an edge model using the trained, modified base model;
• converting the edge model into executable code;
• and
• storing the executable code in a memory.