BAGEL

BAGEL by ByteDance-Seed is an Apache 2.0 open-source unified multimodal model designed for advanced image/text understanding, generation, editing, and navigation. It offers capabilities comparable to proprietary systems like GPT-4o and Gemini 2.0. BAGEL can be fine-tuned, distilled, and deployed anywhere, providing precise, accurate, and photorealistic outputs through its natively multimodal architecture.

Key Features of BAGEL

• 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

Use Cases for BAGEL

• 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