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Update app.py
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app.py
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@@ -307,9 +307,10 @@ with block:
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<img class="logo" src="https://huggingface.co/datasets/philschmid/assets/resolve/main/aws-neuron_hf.png" alt="Hugging Face Habana Logo"
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style="margin: auto; max-width: 14rem;">
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<h1 style="font-weight: 900; margin-bottom: 7px;margin-top:5px">
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Stable Diffusion XL on AWS INF2 ⚡
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</h1>
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<p style="margin-bottom: 10px; font-size: 94%; line-height: 23px;">
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SDXL is a high quality text-to-image model from Stability AI. This demo is running on <a style="text-decoration: underline;" href="https://aws.amazon.com/ec2/instance-types/inf2/?nc1=h_ls">AWS Inferentia2</a>, to achieve efficient and cost-effective inference of 1024×1024 images. <a href="https://www.philschmid.de/inferentia2-stable-diffusion-xl" target="_blank">How does it work?</a>
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</p>
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</div>
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<img class="logo" src="https://huggingface.co/datasets/philschmid/assets/resolve/main/aws-neuron_hf.png" alt="Hugging Face Habana Logo"
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style="margin: auto; max-width: 14rem;">
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<h1 style="font-weight: 900; margin-bottom: 7px;margin-top:5px">
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Latent Consistent Stable Diffusion XL on AWS INF2 ⚡
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</h1>
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<p style="margin-bottom: 10px; font-size: 94%; line-height: 23px;">
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Latent Consistency Models (LCMs) were proposed in Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference by Simian Luo, Yiqin Tan, Longbo Huang, Jian Li, and Hang Zhao. LCMs enable inference with fewer steps on any pre-trained LDMs, including Stable Diffusion and SDXL.
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SDXL is a high quality text-to-image model from Stability AI. This demo is running on <a style="text-decoration: underline;" href="https://aws.amazon.com/ec2/instance-types/inf2/?nc1=h_ls">AWS Inferentia2</a>, to achieve efficient and cost-effective inference of 1024×1024 images. <a href="https://www.philschmid.de/inferentia2-stable-diffusion-xl" target="_blank">How does it work?</a>
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</p>
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</div>
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