Seedream 2.0

What is Seedream 2.0

Seedream 2.0 is a native Chinese-English bilingual launched by ByteDance's Beanbag Big Model teamImage GenerationBase model. The model has served hundreds of millions of C-end users since it was launched on Beanbag APP and Instant Dream platform in early December 2024, and has been widely acclaimed by professional designers and AIGC enthusiasts for its excellent Chinese and English comprehension and image generation capabilities.

Seedream 2.0 Main Features

The main function of Seedream 2.0 is to generate images based on text cues provided by the user. It supports not only English cue words, but also Chinese cue words natively, and is able to accurately render Chinese and English text in the image. In addition, the model is highly aesthetically pleasing and text-rendering, and is capable of generating detailed and well-structured images.

Seedream 2.0 Technical Features

1. Bilingual comprehension and rendering: Seedream 2.0 realizes the spatial mapping alignment of textual Embedding with visual features by large-scale text-image pair fine-tuning Decoder-Only architecture of Large Language Model (LLM). Meanwhile, a specialized dataset is constructed for scenes such as Chinese calligraphy, dialect slang, and technical terms, which strengthens the model's in-depth understanding and perception of cultural symbols.
2. Bimodal code fusion: The model constructs a bimodal coding fusion system, where LLM is responsible for parsing text semantics, while the ByT5 glyph alignment model focuses on portraying the glyph features of the text. This design allows rendering attributes such as font, color, size, position, etc. to no longer rely on predefined templates, but to be directly described by the LLM for end-to-end training of text features.
3. Triple Upgrade DiT Architecture: Based on the MMDiT architecture of SD3, Seedream 2.0 has been upgraded twice. First, QK-Norm is introduced to suppress the numerical fluctuation of the attention matrix, which is combined with the Full Segmented Data Parallelism (FSDP) strategy to improve the training stability; second, the Scaling ROPE technical scheme is designed to adjust the coding by dynamic scaling factor to keep the central region of the image spatially consistent under different aspect ratios, which realizes the generation of multi-resolution images.
4. Alignment with Human Feedback (RLHF): During the post-training process of the model, the Seedream 2.0 team employed human feedback alignment techniques. The self-developed reward model and feedback learning algorithm significantly improved the overall performance of the model in terms of graphic consistency, aesthetic effect, structural correctness and text rendering.

Seedream 2.0 Usage Scenarios

Seedream 2.0 is suitable for a wide range of image generation scenarios, including but not limited to:

1. Creative Design: Designers can use the model to quickly generate creative images that meet requirements and improve design efficiency.
2. EdutainmentIn the education field, teachers can use the model to generate image materials for teaching; in the entertainment field, users can generate personalized game characters, wallpapers, and so on.
3. advertising marketing: Advertisers can utilize the model to generate appealing advertisement images and enhance advertising effectiveness.

Seedream 2.0 Operating Instructions

The basic steps for generating an image using the Seedream 2.0 model are as follows:

1. Select Platform: Log in to your account on the Beanbag App or the Instant Dream platform.
2. Enter the prompt: Enter prompt words in English and Chinese in the specified input box to describe the content of the image you want to generate.
3. Generating images: Click on the Generate button and the model will generate the appropriate image based on the cue word.
4. Adjustment and optimization: Users can adjust and optimize the generated image as needed, such as modifying the color and size.

Seedream 2.0 Recommended Reasons

1. Excellent bilingual comprehension and rendering skills: Seedream 2.0 is able to accurately understand Chinese and English cue words and generate images corresponding to them. For Chinese-speaking users, this model is more relevant than mainstream models such as Midjourney.
2. Highly aesthetic and text rendering effects: The images generated by this model are highly aesthetic and text-rendering, rich in detail and well-structured.
3. Wide range of application scenarios: Seedream 2.0 is suitable for a wide range of image generation scenarios and can meet the needs of different users.
4. Continuous technological innovation: Byte Jump's Beanbag Big Model team is constantly innovating in image generation technology, and Seedream 2.0, one of its core models, will continue to be optimized and upgraded in the future.