

Qwen2.5 VL
Overview :
Qwen2.5-VL is the latest flagship visual language model released by the Qwen team, representing a significant advancement in the field of visual language models. It can not only recognize common objects but also analyze complex content in images, such as text, charts, and icons, and supports understanding of long videos and event localization. The model performs exceptionally well in various benchmark tests, particularly excelling in document understanding and visual agent tasks, showcasing strong visual comprehension and reasoning abilities. Its main advantages include efficient multimodal understanding, powerful long video processing capabilities, and flexible tool invocation features, making it suitable for a variety of application scenarios.
Target Users :
This product is designed for enterprises and individuals needing efficient processing of image and video content, such as in fintech, content creation, education, and scientific research. It helps users quickly extract key information from images and videos, thus enhancing work efficiency, especially in scenarios involving large volumes of visual data.
Use Cases
In the financial sector, Qwen2.5-VL can be used to analyze and extract key information from documents such as invoices and receipts, improving efficiency in financial processing.
In the education field, this model can assist teachers in quickly generating teaching materials by analyzing charts from textbooks and producing explanatory text.
In content creation, Qwen2.5-VL can automate the tagging and summary generation of video content, helping creators quickly organize their video footage.
Features
Powerful visual recognition capabilities, able to identify a wide range of image content.
Supports long video understanding, capable of processing videos longer than one hour and locating key events.
Offers visual agent functionality, allowing it to act as a visual agent for reasoning and tool invocation.
Supports various formats of visual localization, generating stable coordinate and attribute outputs.
Capable of generating structured outputs suitable for finance, business, and other fields.
Supports multilingual and multidirectional text recognition and understanding.
Unique QwenVL HTML format for parsing complex document layouts.
How to Use
1. Visit [Qwen Chat](https://chat.qwenlm.ai) and select the Qwen2.5-VL-72B-Instruct model.
2. Upload the image or video file that needs processing.
3. Select the appropriate function based on your needs, such as image recognition, video understanding, or document analysis.
4. The model will automatically process and generate results. Users can view and download the output content based on the prompts provided.
5. For complex tasks, the model's tool invocation feature can be used to dynamically obtain the necessary information.
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