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  <br>
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  <div style="text-align: center; font-size: 24px; max-width: 1000px; margin: 0 auto;">
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  HuHu Try-on Turbo is a timestep- and guidance-distilled Rectified Flow Transformer <br>
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- that delivers high-fidelity try-on results at 1024×768 resolution in under 1 second<sup><a href="#note">*</a></sup>, <br>
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  without compromising visual quality.
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  </div>
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  <br>
 
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  <br>
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  <div style="text-align: center; font-size: 24px; max-width: 1000px; margin: 0 auto;">
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  HuHu Try-on Turbo is a timestep- and guidance-distilled Rectified Flow Transformer <br>
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+ that delivers high-fidelity try-on results at 1024×768 resolution in 1 second<sup><a href="#note">*</a></sup>, <br>
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  without compromising visual quality.
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  </div>
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  <br>
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- <div style="text-align: center; font-size: 30px; max-width: 800px; margin: 0 auto;">
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  Key highlights driving our model's exceptional speed and fidelity include: <br>
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  <ul>
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  <li>Parallel DiT architecture with 16-channel VAE, enabling maximum garment fidelity and fine detail retention </li>
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  </ul>
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  <br>
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- <div style="text-align: center; font-size: 24px; max-width: 800px; margin: 0 auto;">
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  <p id="note">
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  Please note that “1 second” refers to the try-on generation’s actual processing time. In pactice, additional pre-processing is applied to the model image with computing intermediate representations, and it may add to the overall latency.<br>
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  However, these pre-processing overheads can be largely optimized with caching, and deliver a near real-time experience in applications.
 
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+ <div style="text-align: center; font-size: 24px; max-width: 800px; margin: 0 auto;">
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  Key highlights driving our model's exceptional speed and fidelity include: <br>
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  <ul>
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  <li>Parallel DiT architecture with 16-channel VAE, enabling maximum garment fidelity and fine detail retention </li>
 
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  </ul>
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  </div>
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  <br>
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+ <div style="text-align: center; font-size: 16px; max-width: 800px; margin: 0 auto;">
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  <p id="note">
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  Please note that “1 second” refers to the try-on generation’s actual processing time. In pactice, additional pre-processing is applied to the model image with computing intermediate representations, and it may add to the overall latency.<br>
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  However, these pre-processing overheads can be largely optimized with caching, and deliver a near real-time experience in applications.