deepseek-ai/
Janus-Pro is a novel autoregressive framework that unifies multimodal understanding and generation. It addresses the limitations of previous approaches by decoupling visual encoding into separate pathways, while still utilizing a single, unified transformer architecture for processing. The decoupling not only alleviates the conflict between the visual encoder’s roles in understanding and generation, but also enhances the framework’s flexibility. Janus-Pro surpasses previous unified model and matches or exceeds the performance of task-specific models. The simplicity, high flexibility, and effectiveness of Janus-Pro make it a strong candidate for next-generation unified multimodal models.
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Random seed for reproducibility, default is random (Default: empty, 0 ≤ seed < 18446744073709552000)
Top P
Top-p sampling parameter, higher values increase diversity (Default: 0.95, 0 ≤ top_p ≤ 1)
Temperature
Temperature parameter, higher values increase randomness (Default: 0.1, 0 ≤ temperature ≤ 1)
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