BAGEL's Core Features
Unified Multimodal Model
Image/Text Understanding
Image/Text Generation (photorealistic images, video frames)
Image Editing (preserves visual identities and details)
Style Transfer
Navigation (in diverse environments)
Compositional Abilities (multi-turn conversations)
Thinking Mode (enhances generation and editing through reasoning)
Pre-training initialized from large language models
Mixture-of-Transformer-Experts (MoT) architecture
BAGEL's Use Cases
Describing and understanding images (e.g., 'Tell me about this picture')
Generating photorealistic images from text prompts (e.g., 'a photo of three antique glass magic potions')
Editing images while preserving details (e.g., 'He squatted down and touched a dog's head')
Transforming image styles (e.g., 'Change to 3D animated style')
Navigating and interacting with virtual environments (e.g., 'After 0.40s, move forward')
Engaging in multi-turn conversations with compositional reasoning (e.g., creating a slogan for a doll)
Refining prompts for detailed and coherent visual outputs using a 'thinking' mode
FAQ from BAGEL
What is BAGEL?
What are BAGEL's core capabilities?
How does BAGEL compare to other models?
When was BAGEL released?
BAGEL Company
BAGEL Company name: ByteDance .
BAGEL Github
BAGEL Github Link: https://github.com/bytedance-seed/BAGEL