#38 · Primary category: Deep Learning Frameworks

LAVIS

deep-learning deep-learning-library image-captioning multimodal-datasets multimodal-deep-learning salesforce vision-and-language vision-framework vision-language-pretraining vision-language-transformer visual-question-anwsering

LAVIS - A One-stop Library for Language-Vision Intelligence

Project last updated:06/02/26

GitHub Stars

11.3K

Forks

1.1K

Contributors

28

License

BSD-3-Clause

Why we included this project

LAVIS is a research library from Salesforce that bundles pretrained vision-and-language models, among them BLIP, InstructBLIP, ALBEF, and CLIP, behind one Python API. Common workloads like image captioning, visual question answering, retrieval, and multimodal classification take a few lines of code rather than hand-built training scripts. It also includes dataset loaders and standardized training and evaluation pipelines, which makes reproducing published results or fine-tuning on your own multimodal data fairly straightforward. The documentation, notebooks, and benchmark suite make it a useful reference for anyone working with these models, though it stays research-oriented rather than a hosted service, so expect to handle deployment yourself.

Articles for this project

No articles for this project yet.

To suggest a topic or contribute an article, contact us.

Related projects in this category