Automating fashion product description generation using machine learning and natural language processing can improve searchability and personalization in ecommerce platforms. This post demonstrates how to fine-tune a vision-language model on a fashion dataset using Amazon SageMaker, and use the predicted attributes to generate product descriptions with the help of Amazon Bedrock.
Table of contents
Vision-language modelsSolution overviewSet up the development environmentLoad and prepare the datasetFine-tune the BLIP-2 model to learn product attributes using SageMakerDeploy the fine-tuned BLIP-2 model and predict product attributes using SageMakerGenerate product descriptions from predicted product attributes using Amazon BedrockConclusionSort: