multimodal model

InternVL2.5-MPO is an advanced multi-modal large-scale language model series built on InternVL2.5 and Mixed Preference Optimization (MPO). This series of models performs well in multi-modal tasks, capable of processing image, text and video data and generating high-quality text responses. The model adopts the 'ViT-MLP-LLM' paradigm to optimize visual processing capabilities through pixel unshuffle operations and dynamic resolution strategies. In addition, the model also introduces support for multiple image and video data, further expanding its application scenarios. InternVL2.5-MPO surpassed multiple benchmark models in multi-modal capability evaluation, proving its leading position in the multi-modal field.