language:
- en
license: cc-by-nc-nd-4.0
library_name: diffusers
tags:
- art
- people
- diffusion
- Cinematic
- Photography
- Landscape
- Interior
- Food
- Car
- Wildlife
- Architecture
- Neuron
- Inferentia
thumbnail: >-
https://storage.googleapis.com/run-diffusion-public-assets/juggernaut-xi/juggernaut-collage-256.webp
base_model: stabilityai/stable-diffusion-xl-base-1.0
pipeline_tag: text-to-image
Juggernaut XI v11 by RunDiffusion (Official) - Neuron
- Amazing prompt adherence ✅
- Massively improved aesthetics
- Better hands, eyes, faces, and compostion
- Fully trained from the ground up using the GPT4 Vision Captioning tool by LEOSAM 🛠️
- Expanded and cleaner dataset with higher quality images 🖼️
- Improved classifications of shots (Full Body, Midshots, Portraits, etc) 📸
- Enhanced text generation capability 📝
- Two different prompting techniques, Natural and Tagging style 🏷️
- Enhanced by RunDiffusion Photo for refinement of details 🧐
Read more about this version here https://rundiffusion.com/juggernaut-xi
Prompting Guide 📘 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
As always, we love our community and feel so lucky to be in this position to bring these awesome tools and models to you amazing diffusers. Thanks for supporting us since our first day back in 2022. Going on TWO YEARS since we first started using generative Ai. Time flies when you're having fun. wow!
Don't forget to follow RunDiffusion team on Twitter.
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")