InternVL2_5-2B
Multi-modal large-scale language model supports deep interaction between images and text
Product Details
InternVL 2.5 is an advanced multi-modal large language model series that builds on InternVL 2.0 by introducing significant training and testing strategy enhancements and data quality improvements while maintaining its core model architecture. The model integrates the newly incrementally pretrained InternViT with various pretrained large language models, such as InternLM 2.5 and Qwen 2.5, using randomly initialized MLP projectors. InternVL 2.5 supports multiple image and video data, with dynamic high-resolution training methods that provide better performance when processing multi-modal data.
Main Features
How to Use
Target Users
The target audience is researchers, developers and enterprises, especially those application scenarios that need to process and understand multi-modal data, such as the combination of images and text. InternVL2_5-2B, with its powerful multi-modal understanding and generation capabilities, is suitable for developing intelligent image-text processing applications, such as image description, visual question answering and multi-modal dialogue systems.
Examples
Use the InternVL2_5-2B model to generate detailed descriptions of product images for e-commerce platforms.
In the field of education, this model is used to provide image-assisted language learning materials to enhance the learning experience.
In the field of security monitoring, video understanding capabilities are used to automatically identify and respond to abnormal behaviors.
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