readme: ---
  license: creativeml-openrail-m
  tags:
  - stable-diffusion
  - text-to-image
  extra_gated_prompt: |-
    This model is open access and available to all, with a CreativeML OpenRAIL-M license further specifying rights and usage.
    The CreativeML OpenRAIL License specifies: 
  
    1. You can't use the model to deliberately produce nor share illegal or harmful outputs or content 
    2. The authors claim no rights on the outputs you generate, you are free to use them and are accountable for their use which must not go against the provisions set in the license
    3. You may re-distribute the weights and use the model commercially and/or as a service. If you do, please be aware you have to include the same use restrictions as the ones in the license and share a copy of the CreativeML OpenRAIL-M to all your users (please read the license entirely and carefully)
    Please read the full license carefully here: https://huggingface.co/spaces/CompVis/stable-diffusion-license
        
  extra_gated_heading: Please read the LICENSE to access this model
  ---
  
  # Stable Diffusion v1 Model Card
  
  Stable Diffusion is a latent text-to-image diffusion model capable of generating photo-realistic images given any text input.
  
  The **Stable-Diffusion-v-1-2** checkpoint was initialized with the weights of the [Stable-Diffusion-v-1-1](https:/steps/huggingface.co/CompVis/stable-diffusion-v-1-1-original) 
  checkpoint and subsequently fine-tuned on 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`.
  
  For more information, please refer to [Training](#training).
  
  #### Download the weights
  - [sd-v1-2.ckpt](https://huggingface.co/CompVis/stable-diffusion-v-1-2-original/resolve/main/sd-v1-2.ckpt)
  - [sd-v1-2-full-ema.ckpt](https://huggingface.co/CompVis/stable-diffusion-v-1-2-original/resolve/main/sd-v1-2-full-ema.ckpt)
  
  This weights are intended to be used with the original [CompVis Stable Diffusion codebase](https://github.com/CompVis/stable-diffusion). If you are looking for the model to use with the D🧨iffusers library, [come here](https://huggingface.co/CompVis/stable-diffusion-v1-2).
  
  ## Model Details
  - **Developed by:** Robin Rombach, Patrick Esser
  - **Model type:** Diffusion-based text-to-image generation model
  - **Language(s):** English
  - **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.
  - **Model Description:** This is a model that can be used to generate and modify images based on text prompts. It is a [Latent Diffusion Model](https://arxiv.org/abs/2112.10752) that uses a fixed, pretrained text encoder ([CLIP ViT-L/14](https://arxiv.org/abs/2103.00020)) as suggested in the [Imagen paper](https://arxiv.org/abs/2205.11487).
  - **Resources for more information:** [GitHub Repository](https://github.com/CompVis/stable-diffusion), [Paper](https://arxiv.org/abs/2112.10752).
  - **Cite as:**
  
        @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}
        }
  
  # Uses
  
  ## Direct Use 
  The model is intended for research purposes only. Possible research areas and
  tasks include
  
  - Safe deployment of models which have the potential to generate harmful content.
  - Probing and understanding the limitations and biases of generative models.
  - Generation of artworks and use in design and other artistic processes.
  - Applications in educational or creative tools.
  - Research on generative models.
  
  Excluded uses are described below.
  
   ### Misuse, Malicious Use, and Out-of-Scope Use
  _Note: This section is taken from the [DALLE-MINI model card](https://huggingface.co/dalle-mini/dalle-mini), but applies in the same way to Stable Diffusion v1_.
  
  
  The model should not be used to intentionally create or disseminate images that create hostile or alienating environments for people. This includes generating images that people would foreseeably find disturbing, distressing, or offensive; or content that propagates historical or current stereotypes.
  #### Out-of-Scope Use
  The model was not trained to be factu