---
license: creativeml-openrail-m
tags:
- stable-diffusion
- text-to-image
inference: false
language:
- en
---

# Rodent Diffusion 1.5 Model Card

Stable Diffusion is a latent text-to-image diffusion model capable of generating photo-realistic images given any text input.
The **Rodent-Diffusion-1-5** checkpoint was created with a custom Stable Diffusion v1.4 model as the base.
From the base model, small merges (0.1-0.3) were included from the following models:
- analogDiffusion
- Knolling Case
- RPGDiffusion
- classicnegative
- cuteRich
- inkpunk
- evoartMj4
- dreamshaper
- deliberate

# Examples

![image](https://huggingface.co/NerdyRodent/rodent-diffusion-1-5/raw/main/00806-Professional%2C_full-colour%2C_HD_digital_portrait_photo_of_a_hipster._Detailed%2C_intricate_hair%2C_high_definition._Focused%2C_crisp%2C_cl_3642035934_Euler%20a.png)

<sub>Professional, full-colour, HD digital portrait photo of a hipster. Detailed, intricate hair, high definition. Focused, crisp, clear and sharp. Ultra-realistic cinematic film still. taken with the Canon m50, 50mm focal. pastel shades AND professional photo of a hipster with vivid, vibrant earthy tones. 1960s Technicolor 16mm celluloid film look. Coffee bar in the background. Decaf latte.
Negative prompt: blurry, smudge, smear, painting, anime, sketch, doodle, illustration, drawing
Steps: 42, Sampler: Euler a, CFG scale: 5.25, Seed: 3642035934, Size: 512x640, Denoising strength: 0.666, Hires upscale: 1.689, Hires upscaler: Latent (bicubic antialiased)
</sub>

## License

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 claims 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 here](https://huggingface.co/spaces/CompVis/stable-diffusion-license)


## Original Stable Diffusion 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}
      }