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@@ -195,7 +195,7 @@ with autocast("cuda"):
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images[0].save("fantasy_landscape.png")
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```
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You can also run this example on colab [](https://colab.research.google.com/github/patil-suraj/Notebooks/blob/master/image_2_image_using_diffusers.ipynb)
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You can also run this example on colab [](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/image_2_image_using_diffusers.ipynb)
-[Unconditional Diffusion with continous scheduler](https://huggingface.co/google/ncsnpp-ffhq-1024)
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**Other Notebooks**:
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*[image-to-image generation with Stable Diffusion](https://colab.research.google.com/github/patil-suraj/Notebooks/blob/master/image_2_image_using_diffusers.ipynb),
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*[image-to-image generation with Stable Diffusion](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/image_2_image_using_diffusers.ipynb),
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*[tweak images via repeated Stable Diffusion seeds](https://colab.research.google.com/github/pcuenca/diffusers-examples/blob/main/notebooks/stable-diffusion-seeds.ipynb),
You can also run this example on colab [](https://colab.research.google.com/github/patil-suraj/Notebooks/blob/master/image_2_image_using_diffusers.ipynb)
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You can also run this example on colab [](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/image_2_image_using_diffusers.ipynb)
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### Tweak prompts reusing seeds and latents
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images[0].save("cat_on_bench.png")
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```
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You can also run this example on colab [](https://colab.research.google.com/github/patil-suraj/Notebooks/blob/master/in_painting_with_stable_diffusion_using_diffusers.ipynb)
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You can also run this example on colab [](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/in_painting_with_stable_diffusion_using_diffusers.ipynb)
|[stochatic_karras_ve](./api/pipelines/stochatic_karras_ve)|[**Elucidating the Design Space of Diffusion-Based Generative Models**](https://arxiv.org/abs/2206.00364)| Unconditional Image Generation |
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**Note**: Pipelines are simple examples of how to play around with the diffusion systems as described in the corresponding papers.
|[stochastic_karras_ve](https://github.com/huggingface/diffusers/blob/main/src/diffusers/pipelines/stochastic_karras_ve)|[**Elucidating the Design Space of Diffusion-Based Generative Models**](https://arxiv.org/abs/2206.00364)|*Unconditional Image Generation*|
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**Note**: Pipelines are simple examples of how to play around with the diffusion systems as described in the corresponding papers.
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images[0].save("fantasy_landscape.png")
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```
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You can also run this example on colab [](https://colab.research.google.com/github/patil-suraj/Notebooks/blob/master/image_2_image_using_diffusers.ipynb)
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You can also run this example on colab [](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/image_2_image_using_diffusers.ipynb)
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### Tweak prompts reusing seeds and latents
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images[0].save("cat_on_bench.png")
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```
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You can also run this example on colab [](https://colab.research.google.com/github/patil-suraj/Notebooks/blob/master/in_painting_with_stable_diffusion_using_diffusers.ipynb)
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You can also run this example on colab [](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/in_painting_with_stable_diffusion_using_diffusers.ipynb)
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