
# 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.
{"language": ["en"], "license": "creativeml-openrail-m", "library_name": "diffusers", "tags": ["stable-diffusion", "stable-diffusion-diffusers", "text-to-image"], "pipeline_tag": "text-to-image", "inference": {"parameters": {"num_inference_steps": 50, "guidance_scale": 5.0, "eta": 1.0}}}
diffusers stable-diffusion stable-diffusion-diffusers text-to-image en arxiv:2305.13301 license:creativeml-openrail-m endpoints_compatible diffusers:StableDiffusionPipeline region:us
TAGS
#diffusers #stable-diffusion #stable-diffusion-diffusers #text-to-image #en #arxiv-2305.13301 #license-creativeml-openrail-m #endpoints_compatible #diffusers-StableDiffusionPipeline #region-us 


# ddpo-incompressibility

This model was finetuned from Stable Diffusion v1-4 using DDPO and a reward function encouraging images that are _not_ JPEG-compressible. See the project website 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 categories (the first 398 categories), but it exhibits some generalization to other prompts.
# ddpo-incompressibility

This model was finetuned from Stable Diffusion v1-4 using DDPO and a reward function encouraging images that are _not_ JPEG-compressible. See the project website 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 categories (the first 398 categories), but it exhibits some generalization to other prompts.
TAGS
#diffusers #stable-diffusion #stable-diffusion-diffusers #text-to-image #en #arxiv-2305.13301 #license-creativeml-openrail-m #endpoints_compatible #diffusers-StableDiffusionPipeline #region-us 
 # ddpo-incompressibility

This model was finetuned from Stable Diffusion v1-4 using DDPO and a reward function encouraging images that are _not_ JPEG-compressible. See the project website 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 categories (the first 398 categories), but it exhibits some generalization to other prompts.