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Some tweaks

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  1. README.md +5 -5
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@@ -21,23 +21,23 @@ We host public weights for Latent Diffusion and Stable Diffusion models. There a
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- Stable Diffusion is a latent text-to-image diffusion model capable of generating photo-realistic images given any text input. For more information about how Stable Diffusion works, please have a look at [🤗's Stable Diffusion with D🧨ffusers blog](hf.co/blog/stable_diffusion).
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  </p>
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  We recommend you use Stable Diffusion with <a href="https://github.com/huggingface/diffusers">🤗 Diffusers library</a>. You can also use the original <a href="https://github.com/compvis/stable-diffusion">CompVis code</a>. There are variants of the weights depending on:
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  <li>The library they are intended for.</li>
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- <li>The training regime. There are 4 training versions: `v1-1` through `v1-4`. Each one was created from the checkpoint of the previous version, and was trained for additional steps in specific variants of the dataset.
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  Please, refer to the details in the following table to choose the weights appropriate for your use.
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- | Model | Library | Details |
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- |--------------------------------|------------|------------------------------------------------------------------------------------------------------------|
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- | stable-diffusion-v1-1 | 🤗Diffusers | 237k steps at resolution 256x256 on laion2B-en. 194k steps at resolution 512x512 on laion-high-resolution. |
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  | stable-diffusion-v1-2 | Diffusers | v1-1 plus: 515k steps at 512x512 on "laion-improved-aesthetics". |
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  | stable-diffusion-v1-3 | Diffusers | v1-2 plus: 195k steps at 512x512 on "laion-improved-aesthetics",with 10% dropping of text-conditioning. |
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  | stable-diffusion-v1-4 | Diffusers | |
 
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+ Stable Diffusion is a latent text-to-image diffusion model capable of generating photo-realistic images given any text input. For more information about how Stable Diffusion works, please have a look at <a href="https://hf.co/blog/stable_diffusion">🤗's Stable Diffusion with 🧨 Diffusers blog.
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  </p>
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  <p>
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  We recommend you use Stable Diffusion with <a href="https://github.com/huggingface/diffusers">🤗 Diffusers library</a>. You can also use the original <a href="https://github.com/compvis/stable-diffusion">CompVis code</a>. There are variants of the weights depending on:
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  <ul>
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  <li>The library they are intended for.</li>
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+ <li>The training regime. There are 4 training versions: <tt>v1-1</tt> through <tt>v1-4</tt>. Each one was created from the checkpoint of the previous version, and was trained for additional steps in specific variants of the dataset.
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  </p>
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  <p>
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  Please, refer to the details in the following table to choose the weights appropriate for your use.
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  </p>
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+ | Model | Library | Details |
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+ |--------------------------------|-------------|------------------------------------------------------------------------------------------------------------|
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+ | [stable-diffusion-v1-1](https://huggingface.co/CompVis/stable-diffusion-v1-1) | 🤗 Diffusers | 237k steps at resolution 256x256 on laion2B-en. 194k steps at resolution 512x512 on laion-high-resolution. |
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  | stable-diffusion-v1-2 | Diffusers | v1-1 plus: 515k steps at 512x512 on "laion-improved-aesthetics". |
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  | stable-diffusion-v1-3 | Diffusers | v1-2 plus: 195k steps at 512x512 on "laion-improved-aesthetics",with 10% dropping of text-conditioning. |
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  | stable-diffusion-v1-4 | Diffusers | |