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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.
Open-source unified multimodal AI for understanding, generation, editing.
- 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
- BAGEL can be used through its unified multimodal interface
- accepting both image and text inputs and outputs in a mixed format. Users can engage in multi-turn conversations
- generate high-fidelity images and video frames
- perform image editing
- apply style transfers
- navigate virtual environments
- and leverage its compositional and thinking modes by providing prompts and interacting with the model.
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