SmolVLM2 500M Video SmolVLM2 500M Video is a lightweight multimodal model designed to analyze video content. The model processes videos, images, and text inputs to generate text outputs whether answering questions about media files, comparing visual content, or transcribing text from images. Despite its compact size, requiring only 1.8GB of GPU RAM for video inference, it delivers robust performance on complex multimodal tasks. This efficiency makes it particularly well suited for on device applications where computational resources may be limited. Model Summary Developed by: Hugging Face 🤗 Model type: Multi modal model (image/multi image/video/text) Language(s) (NLP): English License: Apache 2.0 Architecture: Based on Idefics3 (see technical summary) Resources Demo: Video Highlight Generator Blog: Blog post Uses SmolVLM2 can be used for inference on multimodal (video / image / text) tasks where the input consists of text queries along with video or one or more images. Text and media files can be interleaved arbitrarily, enabling tasks like captioning, visual question answering, and storytelling based on visual content. The model does not support image or video generation. To fine…
We use cookies for essential functionality and analytics. You can accept or reject analytics cookies.Cookie policy