metadata

license: mit
library_name: diffusers
pipeline_tag: text-to-image

Mann-E Dreams

Description

This is the newest SDXL based model from Mann-E platform, which is a generative AI startup based in Iran. This model used thousands of midjourney generated images in order to make it possible to make high-quality images. Also, we've used a lot of tricks in order to make it possible to make the model as fast as SDXL Turbo or any other model which claims to be fast.

The model has been mostly developed by Founder and CEO of Mann-E, Muhammadreza Haghiri and a team of four. We spent months on collecting the data, labeling them and training this model. The model is mostly uncensored and tested with Automatic1111.

Model Settings

CLIP Skip: 1 or 2 are both fine. 1 gives better results.
Steps: 6-10. Usually 8 is perfect.
CFG Scale: 2-4.
Scale: 768x768 and 832x832 are just fine. Higher isn't tested. For 16:9 just try 1080x608
Sampler : DPM++ SDE Karras

Use it with diffusers

from diffusers import DiffusionPipeline, DPMSolverSinglestepScheduler
import torch

pipe = DiffusionPipeline.from_pretrained(
    "mann-e/Mann-E_Dreams", torch_dtype=torch.float16
).to("cuda")

#This is equivalent to DPM++ SDE Karras, as noted in https://huggingface.co/docs/diffusers/main/en/api/schedulers/overview
pipe.scheduler = DPMSolverSinglestepScheduler.from_config(pipe.scheduler.config, use_karras_sigmas=True)

image = pipe(
  prompt="a cat in a bustling middle eastern city",
  num_inference_steps=8,
  guidance_scale=3,
  width=768,
  height=768,
  clip_skip=1
).images[0]
image.save("a_cat.png")

Additional Notes

SDXL 1.0 LoRas are working just fine with the model.
ControlNet, IPAdapter, InstantID are just fine.

Donations

Tron/USDT (TRC20) : TPXpiWACUZXtUszDbpLeDYR75NQTwngD8o
ETH (ERC20): 0x44e262f121b88bcb21caac3d353edd78c3717e08