Janus-Pro-1B
| Property | Value |
|---|---|
| Author | deepseek-ai |
| License | MIT License (code), DeepSeek Model License (model) |
| Base Model | DeepSeek-LLM-1.5b-base |
| Vision Encoder | SigLIP-L (384x384 input) |
What is Janus-Pro-1B?
Janus-Pro-1B is an innovative autoregressive framework that unifies multimodal understanding and generation in a single architecture. The model's unique approach lies in its decoupled visual encoding pathways while maintaining a unified transformer architecture for processing. This design choice effectively resolves conflicts between visual encoding roles in understanding and generation tasks.
Implementation Details
The model is built upon the DeepSeek-LLM-1.5b-base architecture and implements two distinct visual processing pathways. For multimodal understanding, it employs SigLIP-L as the vision encoder, supporting 384x384 image inputs. The image generation component utilizes a specialized tokenizer with a 16x downsample rate.
- Decoupled visual encoding pathways for enhanced flexibility
- Unified transformer architecture for efficient processing
- Built on DeepSeek-LLM base model
- SigLIP-L vision encoder integration
Core Capabilities
- Multimodal understanding and interpretation
- Image generation with high fidelity
- Unified processing of visual and textual information
- Flexible architecture supporting multiple tasks
Frequently Asked Questions
Q: What makes this model unique?
Janus-Pro-1B's uniqueness lies in its decoupled visual encoding approach while maintaining a unified architecture, allowing it to match or exceed task-specific models' performance while offering greater flexibility.
Q: What are the recommended use cases?
The model is ideal for applications requiring both visual understanding and generation capabilities, such as image analysis, visual question answering, and image generation tasks, all within a single unified framework.
