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Fastvlm
Overview :
FastVLM is an efficient visual encoding model designed specifically for visual language models. It uses the innovative FastViTHD hybrid visual encoder to reduce the time required for encoding high-resolution images and the number of output tokens, resulting in excellent performance in both speed and accuracy. FastVLM is primarily positioned to provide developers with powerful visual language processing capabilities, applicable to various scenarios, particularly performing excellently on mobile devices that require rapid response.
Target Users :
The product is suitable for researchers and developers engaged in artificial intelligence, computer vision, and natural language processing, especially those who hope to achieve efficient image and text interaction on mobile devices. The efficiency and flexibility of FastVLM make it an ideal choice for rapid iterative development.
Use Cases
Quickly identify and describe image content in mobile applications.
Enable real-time image and text interaction functions such as intelligent customer service.
Combine image understanding and language description in educational software.
Features
FastViTHD Hybrid Visual Encoder: Effectively reduces token output and enhances encoding efficiency.
Significantly shortens Time-to-First-Token (TTFT), improving user experience.
Supports multiple variants to adapt to different application needs and hardware configurations.
Provides mobile device-compatible inference capabilities, expanding use cases.
Includes detailed usage instructions and model export tools, facilitating integration by developers.
How to Use
Clone or download the FastVLM code repository.
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Install dependencies and create a conda environment.
Download pre-trained model checkpoints.
Run inference scripts, input images and prompt information.
View and analyze the results of the model output.
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