Model description
from diffusers import DiffusionPipeline
import torch
Load the model (with float16 precision for GPU)
pipe = DiffusionPipeline.from_pretrained(
"Heartsync/NSFW-Uncensored",
torch_dtype=torch.float16
)
pipe.to("cuda") # Move to GPU
Generate an image with a simple prompt
prompt = "Woman in an elegant dress standing by a window, detailed lighting, 8k"
negative_prompt = "low quality, blurry, deformed"
Create the image
image = pipe(
prompt=prompt,
negative_prompt=negative_prompt,
num_inference_steps=30,
guidance_scale=7.5
).images[0]
Save the image
image.save("generated_image.png")
Advanced example - fixed seed and additional parameters
import numpy as np
Set seed for reproducible results
seed = 42
generator = torch.Generator("cuda").manual_seed(seed)
Advanced parameter settings
prompt = "A dramatic scene with explicit details, cinematic lighting, high resolution"
image = pipe(
prompt=prompt,
negative_prompt="ugly, deformed, disfigured, poor quality, low resolution",
num_inference_steps=50, # More steps for higher quality
guidance_scale=8.0, # Increase prompt fidelity
width=768, # Adjust image width
height=768, # Adjust image height
generator=generator # Fixed seed
).images[0]
image.save("high_quality_image.png")
Trigger words
You should use At full blast to trigger the image generation.
Download model
Download them in the Files & versions tab.
