EAGLE

Exploration of the design space for multimodal large language models

CommonProductProgrammingMultimodal LearningLarge Language Models

EAGLE is a series of high-resolution, vision-centric multimodal large language models (LLMs) designed to enhance the perception capabilities of multimodal LLMs through a combination of visual encoders and varied input resolutions. The model features a 'CLIP+X' fusion based on channel connections, suitable for visual experts trained on different architectures (ViT/ConvNets) and domains (detection/segmentation/OCR/SSL). The EAGLE model family supports input resolutions over 1K and excels in multimodal LLM benchmarks, particularly in resolution-sensitive tasks such as optical character recognition and document understanding.

Supports input resolutions over 1K
suitable for high-resolution images and document understanding.
Utilizes CLIP+X fusion technology
integrating various visual encoder architectures and knowledge.
Demonstrates outstanding performance in multimodal LLM benchmarks
especially in optical character recognition and document understanding tasks.
Provides pre-trained models and fine-tuning data for easy use by researchers and developers.
Supports various input types
including images
text

\The EAGLE model is suitable for researchers
developers
and enterprises
particularly those who need to handle high-resolution images and document understanding tasks. It helps improve model performance in visual and language understanding tasks
while providing a flexible model architecture to adapt to various application scenarios.\

In autonomous driving
the EAGLE model can be used to understand and process road signs and traffic signals.
In medical image analysis
the EAGLE model can help identify and classify patterns and anomalies in medical images.
In intelligent customer service systems

1. Clone the EAGLE codebase to your local environment.
2. Create a Python environment and install the necessary dependencies.
3. Prepare pre-training and fine-tuning data.
4. Select the appropriate model architecture and configuration based on your needs.
5. Run the pre-training script to initiate the model's pre-training.

Visit

EAGLE Visit Over Time

Monthly Visits

494758773

Bounce Rate

37.69%

Page per Visit

5.7

Visit Duration

00:06:29

EAGLE Visit Trend

EAGLE Visit Geography

EAGLE Traffic Sources

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