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README.md
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Welcome to CompVis!
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<p>
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We host public weights for Latent Diffusion and Stable Diffusion models. There are several options to choose from, please check the details below.
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</p>
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<
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Stable Diffusion Models
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<p>
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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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<p>
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We recommend you use Stable Diffusion with
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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: `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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</p>
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<tr>
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<th class="tg-0pky">Model</th>
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<th class="tg-0pky">Library</th>
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<th class="tg-0pky">Details</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<td class="tg-0pky"><a href="https://huggingface.co/CompVis/stable-diffusion-v-1-1" target="_blank" rel="noopener noreferrer">stable-diffusion-v1-1</a></td>
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<td class="tg-0pky"><a href="https://github.com/huggingface/diffusers" target="_blank" rel="noopener noreferrer"><span style="font-weight:400">🤗</span></a><a href="https://github.com/huggingface/diffusers" target="_blank" rel="noopener noreferrer">Diffusers</a></td>
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<td class="tg-0pky">237k steps at resolution 256x256 on laion2B-en.<br>194k steps at resolution 512x512 on laion-high-resolution.</td>
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</tr>
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<td class="tg-0pky"><a href="https://huggingface.co/CompVis/stable-diffusion-v-1-2" target="_blank" rel="noopener noreferrer"><span style="color:#905">stable-diffusion-v1-2</span></a></td>
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<td class="tg-0pky"><a href="https://github.com/huggingface/diffusers" target="_blank" rel="noopener noreferrer"><span style="font-weight:400;font-style:normal;text-decoration:none">Diffusers</span></a></td>
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<td class="tg-0pky">v1-1 plus:<br>515k steps at 512x512 on "laion-improved-aesthetics".</td>
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</tr>
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<td class="tg-0pky"><a href="https://huggingface.co/CompVis/stable-diffusion-v-1-3" target="_blank" rel="noopener noreferrer"><span style="color:#905">stable-diffusion-v1-3</span></a></td>
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<td class="tg-0pky"><a href="https://github.com/huggingface/diffusers" target="_blank" rel="noopener noreferrer"><span style="font-weight:400;font-style:normal;text-decoration:none">Diffusers</span></a></td>
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<td class="tg-0pky">v1-2 plus:<br>195k steps at 512x512 on "laion-improved-aesthetics",with 10% dropping of text-conditioning.</td>
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</tr>
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<td class="tg-0pky"><a href="https://huggingface.co/CompVis/stable-diffusion-v-1-4" target="_blank" rel="noopener noreferrer"><span style="color:#905">stable-diffusion-v1-4</span></a></td>
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<td class="tg-0pky"><a href="https://github.com/huggingface/diffusers" target="_blank" rel="noopener noreferrer"><span style="font-weight:400;font-style:normal;text-decoration:none">Diffusers</span></a></td>
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<td class="tg-0pky"></td>
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</tr>
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<td class="tg-0pky"><a href="https://huggingface.co/CompVis/stable-diffusion-v-1-1-original" target="_blank" rel="noopener noreferrer"><span style="color:#905">stable-diffusion-v1-1-original</span></a></td>
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<td class="tg-0pky"><a href="https://github.com/compvis/stable-diffusion" target="_blank" rel="noopener noreferrer">CompVis</a></td>
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<td class="tg-0pky">237k steps at resolution 256x256 on laion2B-en.<br>194k steps at resolution 512x512 on laion-high-resolution.</td>
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</tr>
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<td class="tg-0pky"><a href="https://huggingface.co/CompVis/stable-diffusion-v-1-2-original" target="_blank" rel="noopener noreferrer"><span style="color:#905">stable-diffusion-v1-2-original</span></a></td>
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<td class="tg-0pky"><a href="https://github.com/compvis/stable-diffusion" target="_blank" rel="noopener noreferrer"><span style="font-weight:400;font-style:normal;text-decoration:none">CompVis</span></a></td>
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<td class="tg-0pky">v1-1 plus:<br>515k steps at 512x512 on "laion-improved-aesthetics".</td>
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</tr>
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<td class="tg-0pky"><a href="https://huggingface.co/CompVis/stable-diffusion-v-1-3-original" target="_blank" rel="noopener noreferrer"><span style="color:#905">stable-diffusion-v1-3-original</span></a></td>
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<td class="tg-0pky"><a href="https://github.com/compvis/stable-diffusion" target="_blank" rel="noopener noreferrer"><span style="font-weight:400;font-style:normal;text-decoration:none">CompVis</span></a></td>
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<td class="tg-0pky">v1-2 plus:<br>195k steps at 512x512 on "laion-improved-aesthetics",<br>with 10% dropping of text-conditioning.</td>
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</tr>
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<tr>
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<td class="tg-0pky"><a href="https://huggingface.co/CompVis/stable-diffusion-v-1-4-original" target="_blank" rel="noopener noreferrer"><span style="color:#905">stable-diffusion-v1-4-original</span></a></td>
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<td class="tg-0pky"><a href="https://github.com/compvis/stable-diffusion" target="_blank" rel="noopener noreferrer"><span style="font-weight:400;font-style:normal;text-decoration:none">CompVis</span></a></td>
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<td class="tg-0pky"></td>
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</tr>
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</tbody>
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</table>
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pinned: false
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---
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<p>
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Welcome to CompVis!
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</p>
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<p>
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We host public weights for Latent Diffusion and Stable Diffusion models. There are several options to choose from, please check the details below.
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</p>
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<p>
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<b>Stable Diffusion Models</b>
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</p>
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<p>
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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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<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: `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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</p>
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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-v1-1-original | CompVis | 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-original | CompVis | v1-1 plus: 515k steps at 512x512 on "laion-improved-aesthetics". |
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| stable-diffusion-v1-3-original | CompVis | 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-original | CompVis | |
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