language:
- en
tags:
- stable-diffusion
- text-to-image
license: bigscience-bloom-rail-1.0
inference: false
thumbnail: >-
https://imagedelivery.net/_wFNZAzgWNWPmneM1cyjcw/artifact/449d42a8-28c5-44da-afd7-28d7e29a264c/public
pony-soup-v2
Pony Diffusion V4 is now live!
pony-diffusion is a latent text-to-image diffusion model that has been conditioned on high-quality pony, furry and other non photorealistic SFW and NSFW images through fine-tuning.
WARNING: This model is capable of producing NSFW content so it's recommended to use 'safe' tag in prompt in combination with negative prompt for image features you may want to suppress (i.e. nudity).
Please join PurpleSmartAI Discord to use this model with our free SD bot and get early access to pony-diffusion-v4.
You can see more samples at PurpleSmartAI
PyTorch Model(Use this with Automatic1111 or other SD UIs)
Model Description
TBD
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:
- You can't use the model to deliberately produce nor share illegal or harmful outputs or content
- 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
- 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
Downstream Uses
This model can be used for entertainment purposes and as a generative art assistant.
Example Code
import torch
from torch import autocast
from diffusers import StableDiffusionPipeline, DDIMScheduler
model_id = "AstraliteHeart/pony-soup-v2"
device = "cuda"
pipe = StableDiffusionPipeline.from_pretrained(
model_id,
torch_dtype=torch.float16,
revision="fp16",
scheduler=DDIMScheduler(
beta_start=0.00085,
beta_end=0.012,
beta_schedule="scaled_linear",
clip_sample=False,
set_alpha_to_one=False,
),
)
pipe = pipe.to(device)
prompt = "pinkie pie anthro portrait wedding dress veil intricate highly detailed digital painting artstation concept art smooth sharp focus illustration Unreal Engine 5 8K"
with autocast("cuda"):
image = pipe(prompt, guidance_scale=7.5)["sample"][0]
image.save("cute_poner.png")
Team Members and Acknowledgements
This project would not have been possible without the incredible work by the CompVis Researchers.
In order to reach us, you can join our Discord server.