MiningGPT -- A Domain-Specific Large Language Model for the Mining Industry
This work addresses the need for domain-specific AI tools in the mining industry, which is economically significant globally, but it is incremental as it builds on existing models.
The authors tackled the problem of large language models lacking domain-specific understanding by developing MiningGPT, a 7B parameter model for the mining industry, which achieved a 14% higher mining domain knowledge test score compared to its parent model Mistral 7B instruct.
Recent advancements of generative LLMs (Large Language Models) have exhibited human-like language capabilities but have shown a lack of domain-specific understanding. Therefore, the research community has started the development of domain-specific LLMs for many domains. In this work we focus on discussing how to build mining domain-specific LLMs, as the global mining industry contributes significantly to the worldwide economy. We report on MiningGPT, a mining domain-specific instruction-following 7B parameter LLM model which showed a 14\% higher mining domain knowledge test score as compared to its parent model Mistral 7B instruct.