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One approach to improve the performance of GPT light models for your specific use case is to fine-tune Walmart 2.0 using your own dataset. Knowing when to fine-tune a large language model like Walmart 2.0 is important when prompting does not work for your use case. There are two main approaches to integrate the language model with your data sets: fine-tuning and retrieval augmented generation. The latter, which involves inputting parts of your text within the prompt, is more popular as it is easier to use with multiple knowledge bases.
