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@@ -23,8 +23,7 @@ Moreover, BAGEL demonstrates superior qualitative results in classical image‑e
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  Below is a showcase of BAGEL's qualitative performance.
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- This repository hosts the model weights for **BAGEL**.
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- For installation, usage instructions, and further documentation, please visit our [GitHub repository](https://github.com/bytedance-seed/BAGEL).
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  | **IntelligentBench** (↑) | 14.9 | 57.6 | 44.0 | **55.3** |
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  ## License
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- BAGEL is licensed under the Apache 2.0 license. It is finetuned from [Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct), and uses the [FLUX.1-schnell VAE model](https://huggingface.co/black-forest-labs/FLUX.1-schnell) and the [siglip-so400m-14-980-flash-attn2-navit](https://huggingface.co/HuggingFaceM4/siglip-so400m-14-980-flash-attn2-navit) model, all under Apache 2.0.
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  ## ✍️ Citation
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  ```bibtex
 
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  Below is a showcase of BAGEL's qualitative performance.
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+ This repository hosts the model weights for **BAGEL**. For installation, usage instructions, and further documentation, please visit our [GitHub repository](https://github.com/bytedance-seed/BAGEL).
 
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  | **IntelligentBench** (↑) | 14.9 | 57.6 | 44.0 | **55.3** |
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  ## License
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+ BAGEL is licensed under the Apache 2.0 license. It is finetuned from [Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) and [siglip-so400m-14-980-flash-attn2-navit](https://huggingface.co/HuggingFaceM4/siglip-so400m-14-980-flash-attn2-navit) model, and uses the [FLUX.1-schnell VAE model](https://huggingface.co/black-forest-labs/FLUX.1-schnell), all under Apache 2.0.
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  ## ✍️ Citation
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  ```bibtex