Multimodal RAG with Vision: From Experimentation to Implementation
This blog post delves into the experimentation journey of fine-tuning a multimodal RAG pipeline to best answer user queries that require both textual and image context. We ran our experiments by systematically testing various approaches, adjusting one configuration setting at a time and using clearly defined evaluation metrics to validate the performance of each component of the RAG pipeline in isolation, as well as the end-to-end inference flow.