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)
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)
-[Unconditional Diffusion with continous scheduler](https://huggingface.co/google/ncsnpp-ffhq-1024)
**Other Notebooks**:
**Other Notebooks**:
*[image-to-image generation with Stable Diffusion](https://colab.research.google.com/github/patil-suraj/Notebooks/blob/master/image_2_image_using_diffusers.ipynb),
*[image-to-image generation with Stable Diffusion](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/image_2_image_using_diffusers.ipynb),
*[tweak images via repeated Stable Diffusion seeds](https://colab.research.google.com/github/pcuenca/diffusers-examples/blob/main/notebooks/stable-diffusion-seeds.ipynb),
*[tweak images via repeated Stable Diffusion seeds](https://colab.research.google.com/github/pcuenca/diffusers-examples/blob/main/notebooks/stable-diffusion-seeds.ipynb),
| [stochatic_karras_ve](./stochatic_karras_ve) | [**Elucidating the Design Space of Diffusion-Based Generative Models**](https://arxiv.org/abs/2206.00364) | Unconditional Image Generation |
| [stochatic_karras_ve](./stochatic_karras_ve) | [**Elucidating the Design Space of Diffusion-Based Generative Models**](https://arxiv.org/abs/2206.00364) | Unconditional Image Generation |
**Note**: Pipelines are simple examples of how to play around with the diffusion systems as described in the corresponding papers.
**Note**: Pipelines are simple examples of how to play around with the diffusion systems as described in the corresponding papers.
...
@@ -143,7 +143,7 @@ with autocast("cuda"):
...
@@ -143,7 +143,7 @@ with autocast("cuda"):
images[0].save("fantasy_landscape.png")
images[0].save("fantasy_landscape.png")
```
```
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)
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)
### Tweak prompts reusing seeds and latents
### Tweak prompts reusing seeds and latents
...
@@ -187,4 +187,4 @@ with autocast("cuda"):
...
@@ -187,4 +187,4 @@ with autocast("cuda"):
images[0].save("cat_on_bench.png")
images[0].save("cat_on_bench.png")
```
```
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)
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)
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)
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)
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)
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)
| [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* |
| [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* |
**Note**: Pipelines are simple examples of how to play around with the diffusion systems as described in the corresponding papers.
**Note**: Pipelines are simple examples of how to play around with the diffusion systems as described in the corresponding papers.
...
@@ -134,7 +134,7 @@ with autocast("cuda"):
...
@@ -134,7 +134,7 @@ with autocast("cuda"):
images[0].save("fantasy_landscape.png")
images[0].save("fantasy_landscape.png")
```
```
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)
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)
### Tweak prompts reusing seeds and latents
### Tweak prompts reusing seeds and latents
...
@@ -179,4 +179,4 @@ with autocast("cuda"):
...
@@ -179,4 +179,4 @@ with autocast("cuda"):
images[0].save("cat_on_bench.png")
images[0].save("cat_on_bench.png")
```
```
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)
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)
