X-PLUG/mPLUG-Owl

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2539 stars · 189 forks observed · 2026-10-03

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

mPLUG-Owl is a family of open-source multimodal large language models that combine visual encoders with LLMs (built on LLaMA) for image and video understanding plus dialogue. It includes mPLUG-Owl, Owl2, and Owl3 with pretrained weights and training/inference code released on HuggingFace.

Use cases

• chat with an AI about images
• build a multimodal chatbot that understands pictures
• run visual question answering on images and videos
• fine-tune a vision-language model on my own data
• understand long sequences of images with an LLM
• describe video content with a large language model
• deploy a GPT-4-like multimodal assistant locally

When to choose

• you need an open-source multimodal LLM for image or video understanding
• you want to fine-tune or research vision-language models
• you need Chinese and English multimodal dialogue support
• you want CVPR-validated architectures with released weights

When to avoid

• you only need text-only LLM inference
• you lack GPU resources for 7B-scale models
• you need a production-ready commercial API rather than research code
• you need audio or speech modality support

Facets

library · maturity active

machine-learning deep-learning llm-inference chatbot image-processing video-processing nlp large-language-models artificial-intelligence computer-vision machine-learning python cross-platform multimodal vision-language-model instruction-tuning huggingface pytorch llama image-understanding video-understanding mplug-owl modelscope natural-language-processing gpu

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markdown · JSON · MCP: product_card(name="X-PLUG/mPLUG-Owl")