Juggernaut XI v11 by RunDiffusion (Official) - Neuron

juggernaut XI photo previews RunDiffusion Logo

  • Amazing prompt adherence โœ…
  • Massively improved aesthetics
  • Better hands, eyes, faces, and compostion
  • Fully trained from the ground up using the GPT4 Vision Captioning tool by LEOSAM ๐Ÿ› ๏ธ
  • Expanded and cleaner dataset with higher quality images ๐Ÿ–ผ๏ธ
  • Improved classifications of shots (Full Body, Midshots, Portraits, etc) ๐Ÿ“ธ
  • Enhanced text generation capability ๐Ÿ“
  • Two different prompting techniques, Natural and Tagging style ๐Ÿท๏ธ
  • Enhanced by RunDiffusion Photo for refinement of details ๐Ÿง

Read more about this version here https://rundiffusion.com/juggernaut-xi

Prompting Guide ๐Ÿ“˜ Because everything has been trained from the ground up, prompting is a bit different. (Simpler, don't worry) @Kandoo has created a guide to help you seamlessly integrate this powerful model into your workflow, enabling you to leverage its advanced capabilities without feeling overwhelmed. Download it here: https://rundiffusion.com/juggernaut-xl#nav

Don't forget to follow RunDiffusion team on Twitter.

https://x.com/RunDiffusion

https://rundiffusion.com?utm_source=huggingface&utm_medium=referral&utm_campaign=juggernautv11

Usage

from diffusers import DPMSolverMultistepScheduler
from optimum.neuron import NeuronStableDiffusionXLPipeline

pipeline = NeuronStableDiffusionXLPipeline.from_pretrained("Shekswess/Juggernaut-XI-v11-Neuron", device_ids=[0, 1])
pipeline.scheduler = DPMSolverMultistepScheduler.from_config(pipeline.scheduler.config)

prompt = "A swirling beautiful exploding scene of magical wonders and surreal ideas and objects with portraits of beautiful woman with silk back to camera, flowers, light, cosmic wonder, nebula, high-resolution"
negative_prompt = "fake eyes, deformed eyes, bad eyes, cgi, 3D, digital, airbrushed, hands, hand"
image = pipeline(prompt=prompt, negative_prompt=negative_prompt).images[0].save("output.png")

Original Model

Model

Precision

BFloat16 (bf16) For Matrix Multiplication Operations.

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