finetuning with my own data at postgresql using azure openai gpt 3.5 16k model #12071
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Hey there, @PradiptaAtByteIQMind-Graph2023! Great to see you diving into another intriguing project. 😊 To fine-tune the Azure OpenAI GPT-3.5 16k model with your own data to improve the accuracy of the RAG application, specifically for NL to SQL using NLSQLTableQueryEngine, you can follow these general steps:
Remember, the specific capabilities and options for fine-tuning may vary based on Azure's offerings and updates to their service. Always refer to the latest Azure OpenAI documentation for the most current information on model training and customization options. Regarding your question about the LlamaIndex repository, it does provide specific methods and utilities for preparing a dataset of natural language queries and corresponding SQL queries. This is evident from the presence of classes like However, as of my last update, I couldn't find any specific methods or utilities in the LlamaIndex repository for fine-tuning the Azure OpenAI GPT-3.5 16k model with user data. The capabilities and options for fine-tuning may vary based on Azure's offerings and updates to their service. Always refer to the latest Azure OpenAI documentation for the most current information on model training and customization options. I hope this information is helpful. If you have any further questions or need more specific guidance, please don't hesitate to ask. Sources
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Hi
is there any methodologies for finetuning the azure open ai with my own data for improve the accuracy of the RAG application i.e. NL to SQL using NLSQLTableQueryEngine?
Thanks
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