Sentence Transformers is a Python library that enables the use and training of embedding and reranker models for applications such as retrieval-augmented generation, semantic search, and others. In a previous article, the author introduced new multimodal capabilities, demonstrating how to use models that process text, images, audio, and video.
In this article, the author explains how to train or finetune these multimodal models on one's own data. This can be useful for those who wish to adapt models to specific tasks and data, which may improve their effectiveness in real-world applications.
editorial commentary
Why it matters
The article may help developers better understand how to adapt multimodal models to their tasks, which could lead to improved performance in real-world applications. However, since the information is based on a single source, additional verification is required to confirm the claims.