Lifu Wang
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Official Repository of the paper: *[Scaling Down Text Encoders of Text-to-Image Diffusion Models](https://github.com/LifuWang-66/ScalingDownTextEncoder/tree/main)*.
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Project Page: https://lifuwang-66.github.io/ScalingDownTE/
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Official Repository of the paper: *[Scaling Down Text Encoders of Text-to-Image Diffusion Models](https://github.com/LifuWang-66/ScalingDownTextEncoder/tree/main)*.
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Project Page: https://lifuwang-66.github.io/ScalingDownTE/
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## Model Descriptions:
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T5-Base distilled from [T5-XXL](https://huggingface.co/google/flan-t5-xxl) using [Flux](https://huggingface.co/runwayml/stable-diffusion-v1-5).
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It is 50 times smaller and retains most capability of T5-XXL.
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## Generation Results:
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<p align="center">
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<img src="teaser.png">
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</p>
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By distilling classifier-free guidance into the model's input, LCM can generate high-quality images in very short inference time. We compare the inference time at the setting of 768 x 768 resolution, CFG scale w=8, batchsize=4, using a A800 GPU.
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<p align="center">
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<img src="speed_fid.png">
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</p>
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