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README.md
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@@ -62,16 +62,12 @@ It is recommended to use the checkpoint with [Stable Diffusion v1-5](https://hug
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has been trained on it.
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Experimentally, the checkpoint can be used with other diffusion models such as dreamboothed stable diffusion.
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**Note**: If you want to process an image to create the auxiliary conditioning, external dependencies are required as shown below:
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1. Install https://github.com/patrickvonplaten/controlnet_aux
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```sh
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$ pip install controlnet_aux==0.3.0
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```
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```
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$ pip install diffusers transformers accelerate
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```
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```python
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import torch
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import os
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## Other released checkpoints v1-1
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The authors released 14 different checkpoints, each trained with [Stable Diffusion v1-5](https://huggingface.co/runwayml/stable-diffusion-v1-5)
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on a different type of conditioning:
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| Model Name | Control Image Overview| Control Image Example | Generated Image Example |
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|---|---|---|---|
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TODO
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### Training
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TODO
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### Blog post
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For more information, please also have a look at the [Diffusers ControlNet Blog Post](https://huggingface.co/blog/controlnet).
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has been trained on it.
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Experimentally, the checkpoint can be used with other diffusion models such as dreamboothed stable diffusion.
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```
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1. Let's install `diffusers` and related packages:
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```
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$ pip install diffusers transformers accelerate
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```
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2. Run code:
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```python
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import torch
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import os
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## Other released checkpoints v1-1
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The authors released 14 different checkpoints, each trained with [Stable Diffusion v1-5](https://huggingface.co/runwayml/stable-diffusion-v1-5)
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on a different type of conditioning:
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| Model Name | Control Image Overview| Control Image Example | Generated Image Example |
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|---|---|---|---|
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TODO
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### Training
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TODO
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### Blog post
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For more information, please also have a look at the [Diffusers ControlNet Blog Post](https://huggingface.co/blog/controlnet).
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