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Internvl3
Overview :
InternVL3 is a multimodal large language model (MLLM) open-sourced by OpenGVLab, possessing superior multimodal perception and reasoning capabilities. This model series includes 7 sizes ranging from 1B to 78B parameters, capable of simultaneously processing various information types such as text, images, and videos, demonstrating excellent overall performance. InternVL3 excels in industrial image analysis and 3D visual perception, with its overall text performance even surpassing the Qwen2.5 series. The open-sourcing of this model provides strong support for multimodal application development and helps promote the application of multimodal technology in more fields.
Target Users :
This product primarily targets AI developers, data scientists, image processing engineers, and researchers in related fields. For AI developers, InternVL3 offers powerful multimodal processing capabilities, helping them quickly build and optimize multimodal applications. For image processing engineers, the model's advantages in industrial image analysis and 3D visual perception make it ideal for handling complex image tasks. Researchers can utilize this model for research and exploration of multimodal technologies, driving development in related fields.
Use Cases
In industrial production, InternVL3 is used to analyze image data from production lines, detect product quality problems in real-time, and improve production efficiency.
In intelligent security, this model processes video data to automatically identify and warn of abnormal behaviors, enhancing security capabilities.
In education, InternVL3 assists teachers in creating multimedia teaching materials, combining text, images, and videos to enrich teaching content.
Features
Supports multiple modality inputs: capable of simultaneously processing various information such as text, images, and videos, meeting diverse needs in different scenarios.
Powerful multimodal perception and reasoning capabilities: excels in handling complex multimodal tasks, accurately understanding and generating related content.
Multi-domain application expansion: covers multiple domains including tool use, GUI agents, industrial image analysis, and 3D visual perception, with wide application scenarios.
Native multimodal pre-training: utilizes advanced pre-training techniques to ensure the model exhibits excellent performance in various tasks.
Flexible model size selection: provides 7 different model sizes ranging from 1B to 78B parameters, meeting the performance and resource needs of different users.
How to Use
Access the ModelScope community to obtain relevant information and download links for the InternVL3 model.
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Select the appropriate model size based on project needs and download the corresponding model file.
Install necessary dependency libraries, such as transformers and torch, ensuring the running environment meets requirements.
Load model weights and configuration files to initialize the model instance.
Prepare input data, including text, images, or videos, and preprocess it according to model requirements.
Call the model for inference, obtain the model output results, and further process the results as needed.
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