| --- |
| license: creativeml-openrail-m |
| language: |
| - en |
| library_name: diffusers |
| pipeline_tag: text-to-image |
| tags: |
| - stable-diffusion |
| - stable-diffusion-diffusers |
| - text-to-image |
| inference: |
| parameters: |
| num_inference_steps: 50 |
| guidance_scale: 5.0 |
| eta: 1.0 |
| --- |
| |
| # ddpo-incompressibility |
|
|
| This model was finetuned from [Stable Diffusion v1-4](https:/CompVis/stable-diffusion-v1-4) using [DDPO](https://arxiv.org/abs/2305.13301) and a reward function encouraging images that are _not_ JPEG-compressible. See [the project website](https://rl-diffusion.github.io/) for more details. |
|
|
| The model was finetuned for 20 iterations with a batch size of 256 samples per iteration. During finetuning, it was prompted with all of the animals in the [Imagenet-1000](https://deeplearning.cms.waikato.ac.nz/user-guide/class-maps/IMAGENET/) categories (the first 398 categories), but it exhibits some generalization to other prompts. |
