llava-vl/llava-next is a large LLaVA-NeXT multimodal model project published on GitHub. It holds a vision-language model implementation that covers image and video understanding and multi-image tasks, together with inference and evaluation materials. It is a Python repository created on March 8, 2024.
A multimodal model (multimodal model) is a model that handles visual information such as images and video together with language. Through three models — LLaVA-OneVision, LLaVA-Video, and LLaVA-NeXT-Interleave — this repository covers single-image, multi-image, video, and 3D tasks. A multi-image task means handling several images together, and a 3D task means handling three-dimensional information.
It is released under the Apache-2.0 license and has 4730 GitHub stars. The README keeps the training pipelines categorized by the existing method and points to lmms-engine for the latest training pipeline.
That said, the scope that can be judged from the provided information is narrow. There are no performance figures or benchmark results, and on the 10-point scale the evaluation record leaves the freshness, technology, and quality items blank, with only momentum at 0.0. There is no release record either, so version-by-version release history cannot be confirmed. Which model is better is hard to judge from this information alone.