Text-to-Image
Diffusers
English
lora
stable-diffusion-xl
style
pixel-art
pixelart
16-bit
retro
game-art
snes
8-bit precision
retro-style
chunky-pixels
snes-era
limited-palette
clean-dithering
nostalgic
vintage
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("strkyyy/pixel-art-16bit")
prompt = "p1x3l16, a wizard's tower on a cliff"
image = pipe(prompt).images[0]16-bit Pixel Art SDXL LoRA for Retro Game-Art
What it does
Retro 16-bit pixel art in the style of classic SNES-era games, featuring a crisp limited palette, clean dithering, chunky readable pixels, and nostalgic game-art composition.
How to use
Trigger: p1x3l16. Suggested strength: 0.85. Recommended sampler: Euler a or Euler a with noise reducer.
Best for
- Wizard's towers on cliffs
- Treasure chests in caves
- Dragons guarding castles
- Cozy tavern interiors
- Heroes walking through deserts
Tips
Adjust the strength to fine-tune the pixel art style. Use higher strengths for more pronounced retro game aesthetics.
Example Prompts
p1x3l16 cyberpunk night cityscape with neon lights glowing in a futuristic urban scene
p1x3l16 hero warrior wielding sword and shield in a fantasy RPG game setting under moonlight
p1x3l16 cozy living room interior with fireplace and bookshelf, warm lighting for a nostalgic home
p1x3l16 space explorer landing on alien planet with strange flora, stars visible through the sky
p1x3l16 character portrait of an adventurer in leather armor, looking determined at dusk setting
p1x3l16 abstract geometric shapes and patterns in vibrant colors for a digital art poster design
Trigger word
Activate with p1x3l16. Recommended strength: 0.9.
Showcase
Usage with diffusers
from diffusers import AutoPipelineForText2Image
import torch
pipe = AutoPipelineForText2Image.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16).to("cuda")
pipe.load_lora_weights("strkyyy/pixel-art-16bit")
image = pipe("p1x3l16, your prompt", num_inference_steps=30).images[0]
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Model tree for strkyyy/pixel-art-16bit
Base model
stabilityai/stable-diffusion-xl-base-1.0