InternVL2_5-4B-MPO-AWQ

A multimodal large language model designed to enhance image and text interaction capabilities.

CommonProductImageMultimodalLarge Language Model

InternVL2_5-4B-MPO-AWQ is a multimodal large language model (MLLM) focused on improving performance in image and text interaction tasks. Based on the InternVL2.5 series and further enhanced through Mixed Preference Optimization (MPO), it can handle a variety of inputs, including single images, multiple images, and video data, making it suitable for complex tasks requiring an understanding of both image and text interactions. With its exceptional multimodal capabilities, InternVL2_5-4B-MPO-AWQ offers a powerful solution for image-to-text and text-to-image tasks.

• Multimodal Understanding: The model can understand and process inputs of both images and text
suitable for scenarios requiring a combination of visual and linguistic information.
• Mixed Preference Optimization (MPO): Optimizes the model's generated responses by combining preference loss
quality loss
and generation loss.
• Support for Multiple Images and Video: The model accommodates inputs of multiple images and video data
expanding its application range.
• Efficient Data Processing: Employs pixel reorganization operations and dynamic resolution strategies to enhance data processing efficiency.
• Pre-training and Fine-tuning: Based on pre-trained InternViT and LLMs
the model is fine-tuned using a randomly initialized MLP projector.

The target audience includes researchers
developers
and enterprise users
especially those looking to implement high-performance AI applications in image and text interaction tasks
such as image recognition

Example 1: Using the InternVL2_5-4B-MPO-AWQ model to automatically describe and tag images on social media.
Example 2: In an e-commerce platform
utilizing the model to generate detailed product descriptions from product images.
Example 3: In the education field
the model can help create interactive learning materials that improve learning efficiency through the integration of images and text.

1. Install the necessary dependencies
such as lmdeploy
to use the model.
2. Load the model by specifying its name 'OpenGVLab/InternVL2_5-4B-MPO-AWQ'.
3. Prepare the input data

Visit

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Monthly Visits

20899836

Bounce Rate

46.04%

Page per Visit

5.2

Visit Duration

00:04:57

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InternVL2_5-4B-MPO-AWQ

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