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Smolvlm2 256M Video Instruct

Developed by HuggingFaceTB
SmolVLM2-256M-Video is a lightweight multimodal model specifically designed for analyzing video content, capable of processing video, image, and text inputs to generate text outputs.
Downloads 22.16k
Release Time : 2/11/2025

Model Overview

This model can process video, image, and text inputs to generate text outputs, suitable for tasks such as answering questions about media files, comparing visual content, or transcribing text from images. Despite its compact size, it requires only 1.38GB of GPU memory for video inference, making it ideal for edge device applications.

Model Features

Lightweight and Efficient
The model is compact, requiring only 1.38GB of GPU memory for video inference, making it suitable for edge device applications with limited computational resources.
Multimodal Processing
Capable of processing video, image, and text inputs simultaneously and generating text outputs.
Edge Device Compatibility
Particularly suitable for edge device applications that may require domain-specific fine-tuning and have limited computational resources.

Model Capabilities

Video Content Analysis
Image Content Analysis
Text Generation
Visual Question Answering
Caption Generation
Visual Content-Based Storytelling

Use Cases

Media Analysis
Video Description Generation
Analyze video content and generate detailed textual descriptions.
Image Question Answering
Answer specific questions about image content.
Content Creation
Visual Storytelling
Generate coherent stories based on provided image or video content.
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