Recently, ByteDance announced the open source of its internally developed VeOmni framework, a unified framework dedicated to multi-modal model training. With the continuous development of artificial intelligence technology, especially the evolution from single-language models to multi-modal models that include text, images, and videos, algorithm engineers face many challenges during the training process, particularly the fragmentation of the training workflow. To address these issues, VeOmni was born.
VeOmni was jointly developed by ByteDance's Seed team and the Volcano Machine Learning platform, aiming to achieve the goals of "unified multi-modal, unified parallel strategy, and unified computing foundation." The framework provides a unified API, integrating various hybrid parallel strategies into one framework, supporting fast training for various models. Whether it is large-scale language models, vision-language models, or video generation models, developers can easily get started.
The framework has significant performance optimization capabilities. For example, it uses a dual optimization strategy for memory computation, which minimizes additional computational overhead while ensuring sufficient memory. In addition, VeOmni adopts a multidimensional parallel system, supporting different parallel primitives, thus effectively reducing memory peaks. The combination of these technologies makes VeOmni perform excellently in actual training, with a training throughput improvement of more than 40% compared to similar open-source solutions.
In terms of distillation acceleration, VeOmni also demonstrates its strong advantages. By integrating various cutting-edge distillation techniques, users can significantly reduce the steps and resource consumption required for model inference, thus accelerating model deployment and application.
The open source of the VeOmni framework not only improves the efficiency of internal model training at ByteDance but also provides a powerful tool for more AI researchers and developers, helping to promote the development of multi-modal AI technology.
Key points:
🌟 VeOmni framework is a unified framework developed by ByteDance specifically for multi-modal model training, aimed at solving the fragmentation issues in the training process.
⚡ This framework significantly improves training efficiency through memory computation and hybrid parallel strategies, with a training throughput increase of over 40%.
🚀 VeOmni integrates cutting-edge distillation technologies, helping users reduce model inference steps and accelerate model deployment.