Emu Series

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1778 stars · 83 forks observed · 2026-08-28

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

Emu3 is a suite of state-of-the-art multimodal models from BAAI trained solely with next-token prediction, tokenizing images, text, and video into a unified discrete space. The repository provides model weights, inference code, and training/fine-tuning scripts for both generation (text-to-image, video prediction) and perception (vision-language understanding) tasks.

Use cases

• generate images from text prompts without diffusion models
• generate or extend videos by predicting next tokens
• build a vision-language chatbot that understands images
• caption images with a multimodal model
• fine-tune a unified multimodal model on custom instruction data
• run multimodal inference with vLLM
• research autoregressive multimodal architectures

When to choose

• you want a single autoregressive model for both multimodal understanding and generation
• you need open weights for text-to-image or video generation research
• you want to avoid diffusion or CLIP-dependent architectures
• you need fine-tuning scripts for multimodal instruction tuning

When to avoid

• you need a lightweight model for CPU-only or edge devices
• you only need a production text-only LLM
• you prefer mature diffusion-based image generation tooling
• you need a hosted API rather than self-hosted weights

Facets

library · maturity active

llm-inference llm-training image-processing video-processing nlp machine-learning artificial-intelligence large-language-models computer-vision image-processing deep-learning python multimodal next-token-prediction autoregressive text-to-image text-to-video vision-language-model transformer model-weights baai image-generation video-generation visual-understanding video natural-language-processing gpu linux

Member repositories

For agents

markdown · JSON · MCP: product_card(name="baaivision/Emu")