# Stable Diffusion

Stable Diffusion is a latent text-to-image diffusion model capable of generating photo-realistic images given any text input.
This model card gives an overview of all available model checkpoints. For more in-detail model cards, please have a look at the model repositories listed under [Model Access](#model-access).

## Stable Diffusion Version 1

For the first version 4 model checkpoints are released.
*Higher* versions have been trained for longer and are thus usually better in terms of image generation quality then *lower* versions. More specifically: 

- **stable-diffusion-v1-1**: The checkpoint is randomly initialized and has been trained on 237,000 steps at resolution `256x256` on [laion2B-en](https://huggingface.co/datasets/laion/laion2B-en).
  194,000 steps at resolution `512x512` on [laion-high-resolution](https://huggingface.co/datasets/laion/laion-high-resolution) (170M examples from LAION-5B with resolution `>= 1024x1024`).
- **stable-diffusion-v1-2**: The checkpoint resumed training from `stable-diffusion-v1-1`.
  515,000 steps at resolution `512x512` on "laion-improved-aesthetics" (a subset of laion2B-en,
filtered to images with an original size `>= 512x512`, estimated aesthetics score `> 5.0`, and an estimated watermark probability `< 0.5`. The watermark estimate is from the LAION-5B metadata, the aesthetics score is estimated using an [improved aesthetics estimator](https://github.com/christophschuhmann/improved-aesthetic-predictor)).
- **stable-diffusion-v1-3**: The checkpoint resumed training from `stable-diffusion-v1-2`. 195,000 steps at resolution `512x512` on "laion-improved-aesthetics" and 10 % dropping of the text-conditioning to improve [classifier-free guidance sampling](https://arxiv.org/abs/2207.12598)
- **stable-diffusion-v1-4**: The checkpoint resumed training from `stable-diffusion-v1-2`. 195,000 steps at resolution `512x512` on "laion-improved-aesthetics" and 10 % dropping of the text-conditioning to improve [classifier-free guidance sampling](https://arxiv.org/abs/2207.12598).
- [**`stable-diffusion-v1-4`**](https://huggingface.co/CompVis/stable-diffusion-v1-4) Resumed from `stable-diffusion-v1-2`.225,000 steps at resolution `512x512` on "laion-aesthetics v2 5+" and 10 % dropping of the text-conditioning to improve [classifier-free guidance sampling](https://arxiv.org/abs/2207.12598).

### Model Access

Each checkpoint can be used both with Hugging Face's [ 🧨 Diffusers library](https://github.com/huggingface/diffusers) or the original [Stable Diffusion GitHub repository](https://github.com/CompVis/stable-diffusion). Note that you have to *"click-request"* them on each respective model repository.

| **[🤗's 🧨 Diffusers library](https://github.com/huggingface/diffusers)**     | **[Stable Diffusion GitHub repository](https://github.com/CompVis/stable-diffusion)** |
| ----------- | ----------- |
| [`stable-diffusion-v1-1`](https://huggingface.co/CompVis/stable-diffusion-v1-1)      | [`stable-diffusion-v-1-1-original`](https://huggingface.co/CompVis/stable-diffusion-v-1-1-original)       |
| [`stable-diffusion-v1-2`](https://huggingface.co/CompVis/stable-diffusion-v1-2)   | [`stable-diffusion-v-1-2-original`](https://huggingface.co/CompVis/stable-diffusion-v-1-2-original)        |
| [`stable-diffusion-v1-3`](https://huggingface.co/CompVis/stable-diffusion-v1-3)   | [`stable-diffusion-v-1-3-original`](https://huggingface.co/CompVis/stable-diffusion-v-1-3-original)        |
| [`stable-diffusion-v1-4`](https://huggingface.co/CompVis/stable-diffusion-v1-4)   | [`stable-diffusion-v-1-4-original`](https://huggingface.co/CompVis/stable-diffusion-v-1-4-original)        |

### Demo

To quickly try out the model, you can try out the [Stable Diffusion Space](https://huggingface.co/spaces/stabilityai/stable-diffusion).

### License

[The CreativeML OpenRAIL M license](https://huggingface.co/spaces/CompVis/stable-diffusion-license) is an [Open RAIL M license](https://www.licenses.ai/blog/2022/8/18/naming-convention-of-responsible-ai-licenses), adapted from the work that [BigScience](https://bigscience.huggingface.co/) and [the RAIL Initiative](https://www.licenses.ai/) are jointly carrying in the area of responsible AI licensing. See also [the article about the BLOOM Open RAIL license](https://bigscience.huggingface.co/blog/the-bigscience-rail-license) on which our license is based.

## Citation

```bibtex
    @InProceedings{Rombach_2022_CVPR,
        author    = {Rombach, Robin and Blattmann, Andreas and Lorenz, Dominik and Esser, Patrick and Ommer, Bj\"orn},
        title     = {High-Resolution Image Synthesis With Latent Diffusion Models},
        booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
        month     = {June},
        year      = {2022},
        pages     = {10684-10695}
    }
```

*This model card was written by: Robin Rombach and Patrick Esser and is based on the [DALL-E Mini model card](https://huggingface.co/dalle-mini/dalle-mini).*

{"license": "creativeml-openrail-m", "tags": ["stable-diffusion", "text-to-image"], "inference": false}
stable-diffusion text-to-image arxiv:2207.12598 license:creativeml-openrail-m has_space region:us
TAGS
#stable-diffusion #text-to-image #arxiv-2207.12598 #license-creativeml-openrail-m #has_space #region-us 

Stable Diffusion
================


Stable Diffusion is a latent text-to-image diffusion model capable of generating photo-realistic images given any text input.
This model card gives an overview of all available model checkpoints. For more in-detail model cards, please have a look at the model repositories listed under Model Access.


Stable Diffusion Version 1
--------------------------


For the first version 4 model checkpoints are released.
*Higher* versions have been trained for longer and are thus usually better in terms of image generation quality then *lower* versions. More specifically:


* stable-diffusion-v1-1: The checkpoint is randomly initialized and has been trained on 237,000 steps at resolution '256x256' on laion2B-en.
194,000 steps at resolution '512x512' on laion-high-resolution (170M examples from LAION-5B with resolution '>= 1024x1024').
* stable-diffusion-v1-2: The checkpoint resumed training from 'stable-diffusion-v1-1'.
515,000 steps at resolution '512x512' on "laion-improved-aesthetics" (a subset of laion2B-en,
filtered to images with an original size '>= 512x512', estimated aesthetics score '> 5.0', and an estimated watermark probability '< 0.5'. The watermark estimate is from the LAION-5B metadata, the aesthetics score is estimated using an improved aesthetics estimator).
* stable-diffusion-v1-3: The checkpoint resumed training from 'stable-diffusion-v1-2'. 195,000 steps at resolution '512x512' on "laion-improved-aesthetics" and 10 % dropping of the text-conditioning to improve classifier-free guidance sampling
* stable-diffusion-v1-4: The checkpoint resumed training from 'stable-diffusion-v1-2'. 195,000 steps at resolution '512x512' on "laion-improved-aesthetics" and 10 % dropping of the text-conditioning to improve classifier-free guidance sampling.
* 'stable-diffusion-v1-4' Resumed from 'stable-diffusion-v1-2'.225,000 steps at resolution '512x512' on "laion-aesthetics v2 5+" and 10 % dropping of the text-conditioning to improve classifier-free guidance sampling.


### Model Access


Each checkpoint can be used both with Hugging Face's Diffusers library or the original Stable Diffusion GitHub repository. Note that you have to *"click-request"* them on each respective model repository.



### Demo


To quickly try out the model, you can try out the Stable Diffusion Space.


### License


The CreativeML OpenRAIL M license is an Open RAIL M license, adapted from the work that BigScience and the RAIL Initiative are jointly carrying in the area of responsible AI licensing. See also the article about the BLOOM Open RAIL license on which our license is based.


*This model card was written by: Robin Rombach and Patrick Esser and is based on the DALL-E Mini model card.*



### Model Access


Each checkpoint can be used both with Hugging Face's Diffusers library or the original Stable Diffusion GitHub repository. Note that you have to *"click-request"* them on each respective model repository. ### Demo


To quickly try out the model, you can try out the Stable Diffusion Space. ### License


The CreativeML OpenRAIL M license is an Open RAIL M license, adapted from the work that BigScience and the RAIL Initiative are jointly carrying in the area of responsible AI licensing. See also the article about the BLOOM Open RAIL license on which our license is based.


*This model card was written by: Robin Rombach and Patrick Esser and is based on the DALL-E Mini model card.*
TAGS
#stable-diffusion #text-to-image #arxiv-2207.12598 #license-creativeml-openrail-m #has_space #region-us 
 ### Model Access


Each checkpoint can be used both with Hugging Face's Diffusers library or the original Stable Diffusion GitHub repository. Note that you have to *"click-request"* them on each respective model repository. ### Demo


To quickly try out the model, you can try out the Stable Diffusion Space. ### License


The CreativeML OpenRAIL M license is an Open RAIL M license, adapted from the work that BigScience and the RAIL Initiative are jointly carrying in the area of responsible AI licensing. See also the article about the BLOOM Open RAIL license on which our license is based.


*This model card was written by: Robin Rombach and Patrick Esser and is based on the DALL-E Mini model card.*
passage: TAGS
#stable-diffusion #text-to-image #arxiv-2207.12598 #license-creativeml-openrail-m #has_space #region-us 
### Model Access


Each checkpoint can be used both with Hugging Face's Diffusers library or the original Stable Diffusion GitHub repository. Note that you have to *"click-request"* them on each respective model repository.### Demo


To quickly try out the model, you can try out the Stable Diffusion Space.### License


The CreativeML OpenRAIL M license is an Open RAIL M license, adapted from the work that BigScience and the RAIL Initiative are jointly carrying in the area of responsible AI licensing. See also the article about the BLOOM Open RAIL license on which our license is based.


*This model card was written by: Robin Rombach and Patrick Esser and is based on the DALL-E Mini model card.*