Text-to-Image
Diffusers
Safetensors
English
StableDiffusionXLPipeline
stable-diffusion
stable-diffusion-xl
Merge
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("Emanon14/NONAMEmix-Vpred_v2", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]NONAMEmix-Vpred
NOTICE
- This is a v-prediction model.
- No longer includes noob AI.
- 99% of this checkpoint is made with RouWei.
Model Description
- Model type: Diffusion-based text-to-image generative model
- Model prompt style: Booru-tags
- License: Fair AI Public License 1.0-SD
Merge Recipe
- RouWei 0.7 vpred (A)
- CyberRealistic XL (B)
- stable-diffusion-xl-base-1.0 (C)
- SPO-SDXL_4k-p_10ep_LoRA_webui (D)
- My LoRA (E)
- Trained by 300 images AI-generated
A + (B - C) * 0.5 = F
F + D + E * 0.5 = This Model v2.0
Recommended settings
- Positive prompts:
masterpiece, best quality
- Negative prompts:
worst quality, low quality, watermark
- CFG: 3-5
- Sampling steps: 28
- Sampler: Euler a
- Supported Resolution:
1024 x 1024, 1152 x 896, 896 x 1152, 1216 x 832, 832 x 1216, 1344 x 768, 768 x 1344, 1536 x 640, 640 x 1536
Hires.fix Setting
- Upscaler: 4x-UltraSharp
- Hires step: 10-15
- Denoising: 0.3-0.4
Thanks
- First of all, to Minthy for RouWei. That has the best prompt following I know of!
- And, of course, thanks for the Animagine. Animagine was the first signpost that led me to use SDXL, and it continues to do so!
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