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Janus is an autoregressive framework that unifies multimodal understanding and generation. Unlike previous approaches that use a single visual encoder for both tasks, Janus decouples visual encoding into separate pathways while utilizing a unified transformer architecture for processing. This decoupling addresses the conflict between visual encoder roles in understanding and generation, enhancing flexibility and performance.
Key features:
Unified framework for multimodal understanding and generation
Decoupled visual encoding pathways
Single, unified transformer architecture for processing
Improved performance in multimodal understanding tasks
Flexibility to select optimal encoding methods for each component
Open source status
The model implementation is available
The model weights are available
Provide useful links for the implementation
The Janus model is developed by DeepSeek AI. Here are the relevant links for implementation:
Model description
Janus is an autoregressive framework that unifies multimodal understanding and generation. Unlike previous approaches that use a single visual encoder for both tasks, Janus decouples visual encoding into separate pathways while utilizing a unified transformer architecture for processing. This decoupling addresses the conflict between visual encoder roles in understanding and generation, enhancing flexibility and performance.
Key features:
Open source status
Provide useful links for the implementation
The Janus model is developed by DeepSeek AI. Here are the relevant links for implementation:
Paper: Janus: Bridging the Gap Between Multimodal Understanding and Generation
GitHub repository: deepseek-ai/Janus
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