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Videollm Online 8b V1plus

Developed by chenjoya
VideoLLM-online is a multimodal large language model based on Llama-3-8B-Instruct, focusing on online video understanding and video-text generation tasks.
Downloads 1,688
Release Time : 6/22/2024

Model Overview

This model combines visual and language processing capabilities, can process video streams up to 10 minutes in real-time, supports frame rate analysis of 2 - 10 frames per second, and is suitable for online video understanding and interactive application scenarios.

Model Features

Real-time video processing
Supports real-time video stream processing at 2 - 10 frames per second and can handle video content up to 10 minutes long
Multimodal understanding
Combines a visual encoder (SigLIP) and a language model (Llama-3) to achieve in-depth understanding of video content
Efficient visual encoding
Adopts a 3x3 token strategy of CLS token + average pooling to maintain efficient processing at 384 resolution
Large-scale training data
Trained using 134K video samples from the Ego4D dataset, covering diverse scenarios

Model Capabilities

Online video understanding
Video content description generation
Multimodal reasoning
Real-time video interaction

Use Cases

Video analysis
Video content summary
Automatically generate content summaries for long videos
Can process 10-minute videos and generate accurate summaries
Real-time video Q&A
Conduct real-time Q&A on the currently playing video content
Supports real-time response at 2 - 10 frames per second
Human-computer interaction
Video-assisted dialogue
A natural language dialogue system based on video content
Can conduct in-depth exchanges with users about video content
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