EAGLE
Exploration of multimodal large language model design space
Product Details
EAGLE is a vision-centered, high-resolution multimodal large language model (LLM) family that enhances the perceptual capabilities of multimodal LLMs by mixing visual encoders and different input resolutions. The model contains channel connection based 'CLIP+X' fusion, suitable for vision experts with different architectures (ViT/ConvNets) and knowledge (detection/segmentation/OCR/SSL). The EAGLE model family supports input resolutions over 1K and achieves excellent results on multi-modal LLM benchmarks, especially on resolution-sensitive tasks such as optical character recognition and document understanding.
Main Features
How to Use
Target Users
The EAGLE model is suitable for researchers, developers and enterprises, especially those who need to process high-resolution images and document understanding tasks. It can help them improve the performance of their models in visual and language understanding tasks, while providing a flexible model architecture to adapt to different application scenarios.
Examples
In the field of autonomous driving, the EAGLE model can be used to understand and process road signs and traffic signals.
In medical image analysis, EAGLE models can help identify and classify patterns and anomalies in medical images.
In intelligent customer service systems, the EAGLE model can be used to understand and respond to queries sent by users through images and text.
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