Baidu has released PaddleMIX 2.0, a multi-modal large model development kit designed to simplify the development process of multi-modal AI applications. It integrates multiple modal data such as images, text, audio and video, and supports multiple application scenarios such as autonomous driving, smart medical care and search engines. PaddleMIX 2.0 provides a rich model library, end-to-end development experience, and high-performance training and inference capabilities, significantly lowering the threshold for multi-modal model development and providing developers with comprehensive tools and support to accelerate AI applications. of innovation.
PaddleMIX2.0 is a multi-modal large model development kit launched by Baidu. It integrates multi-modal data such as graphics, text, audio and video, and comprehensively covers multiple application scenarios such as autonomous driving, smart medical care, and search engines, and promotes AI applications. of innovation. The release of PaddleMIX 2.0 aims to reduce the development difficulty for developers in the multi-modal field and provide support for high-performance algorithms, convenient development, efficient training and complete deployment.
The three major highlights of PaddleMIX2.0 include:
A rich multi-modal model library covers image, text, video, and audio modalities, and has added cutting-edge models such as the LLaVA series.
The end-to-end full-process development experience, including the multi-modal data processing toolbox DataCopilot and Auto modules, simplifies the training process of multi-modal large models.
High-performance large-scale training and promotion capabilities, DiT model supports 3B scale pre-training, leading performance, new MixToken training strategy, significantly improved training throughput.
PaddleMIX2.0 also provides the AppFlow tool, which builds a variety of multi-modal applications through pipeline combination, and the ComfyUI plug-in, which supports multi-modal capabilities and simplifies the operation of AIGC tasks. In addition, PaddleMIX2.0 has significant performance improvements in large-scale pre-training, efficient fine-tuning training and high-performance inference.
Open source project homepage: https://github.com/PaddlePaddle/PaddleMIX
All in all, PaddleMIX 2.0, with its powerful functions and ease of use, provides strong support for the development of multi-modal AI applications, and is worthy of developers' attention and attempts. Its open source nature also further promotes the development and sharing of AI technology.