haidarazmi/lora-pixel-art-characters-datases
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How to use milliyin/pixel_art_characters_lora_flux_nf4 with Diffusers:
pip install -U diffusers transformers accelerate
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("milliyin/pixel_art_characters_lora_flux_nf4")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]Task: Text-to-Image (Pixel Art Characters)
Base: black-forest-labs/FLUX.1-dev β’ Adapter: LoRA (attention layers)
Hardware: Trained on NVIDIA A100
Updated: 2025-08-26
This LoRA adapts FLUX to generate retro pixel-art characters with consistent silhouettes and limited palettes great for game assets, avatars, and concept iterations.
Keep prompts short and style-focused (see tips below).
License defaults to CC BY-NC 4.0 (non-commercial).
import torch
from diffusers import FluxPipeline
pipe = FluxPipeline.from_pretrained(
"black-forest-labs/FLUX.1-dev",
torch_dtype=torch.float16
).to("cuda")
pipe.load_lora_weights("milliyin/pixel_art_characters_lora_flux_nf4")
NEGATIVE_PROMPT = "blurry, low quality, distorted, ugly"
HEIGHT = 512
WIDTH = 512
GUIDANCE_SCALE = 7.5
NUM_INFERENCE_STEPS = 50
SEED = 42
prompt = "pixel art, rpg adventurer, green cloak, clean outline, limited palette, facing forward"
image = pipe(
prompt=prompt,
negative_prompt=NEGATIVE_PROMPT,
height=HEIGHT,
width=WIDTH,
guidance_scale=GUIDANCE_SCALE,
num_inference_steps=NUM_INFERENCE_STEPS,
).images[0]
image.save("sample.png")
Base model
black-forest-labs/FLUX.1-dev