DAMO-NLP-SG/VideoLLaMA2

Health v2 · maintenance only

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1307 stars · 89 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

VideoLLaMA 2 is an open-source video large language model that adds spatial-temporal modeling and audio understanding to video-LLMs. It provides pretrained checkpoints, training and inference code, and demos for video question answering and captioning.

Use cases

• answer questions about videos with an LLM
• generate captions for videos automatically
• build a multimodal chatbot that understands video and audio
• fine-tune a video-language model on custom data
• benchmark zero-shot video question answering
• analyze spatial-temporal content in video clips

When to choose

• you need a ready-to-use open video-LLM with audio support
• you want strong zero-shot video QA and captioning baselines
• you need Apache-2.0 licensed multimodal model code and checkpoints

When to avoid

• you only need image-only vision-language understanding
• you lack GPU resources for large multimodal models
• you need a lightweight production video analytics service rather than a research model

Facets

library · maturity active

machine-learning deep-learning llm-inference llm-training video-processing audio-processing nlp artificial-intelligence large-language-models computer-vision python video-llm multimodal video-question-answering video-captioning audio-understanding spatial-temporal-modeling research video audio natural-language-processing gpu linux

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markdown · JSON · MCP: product_card(name="DAMO-NLP-SG/VideoLLaMA2")