A Tool for Generating Synthetic Data in GenAI for Better NLP Systems
Unbalanced data and the biases they inject into ML models are one of the main problems in ML. We may now readily replace imbalanced training data with synthetic data thanks to the development of potent Generative AI (GenAI) models, notably for Natural Language Processing (NLP) workloads. In situations when Deep Learning models or using LLMs directly are not an option due to factors like the cost of computing, memory, the availability of infrastructure, or the explainability of the model, we can train models using standard ML algorithms for better results. In addition, we still don't entirely trust LLMs despite the impressive efficacy they have demonstrated. LLMs can, however, help us in our work as data professionals and
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