In this video, we dive deep into Bagel, an exciting and fully open-source AI multimodal model. Bagel stands out as it can natively understand and output images, offering capabilities similar to GPT-4 O but as an open-source solution. We explore its functionalities, including image generation, image editing, and unique features like navigation and rotation. We compare Bagel’s performance with other AI models like GPT-4 O and Google Gemini, discussing its potential and areas for improvement. With generous backing from ByteDance and an Apache 2.0 license, Bagel provides a promising platform for developers to fine-tune, distill, and deploy. Join me as I put Bagel through its paces, test its image generation and understanding, and see if it lives up to its potential.
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00:00 Introduction to Bagel: The Open Source AI Model
00:27 Bagel’s Unique Features and Capabilities
01:25 Teaser Video and Project Backing
04:24 Hands-On Testing and Initial Impressions
04:52 Image Generation and Editing Capabilities
07:21 Advanced Features: Spatial Understanding and Thinking Mode
08:54 Comparing Bagel with Other AI Models
16:46 Testing Bagel’s Image Generation with Personal Photos
25:17 Final Thoughts and Conclusion
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