import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("shauray/FLUX-UNCENSORED-merged", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]flux-uncensored
Summary
Flux base model merged with uncensored LoRA. This model is not for those looking for "safe" or watered-down outputs. It’s optimized for real-world use with fewer constraints.
Specs
- Model: Flux base
- LoRA: Uncensored version, merged directly
Usage
pretty straight forward plug-and-play model
from diffusers import FluxPipeline
import torch
pipe = FluxPipeline.from_pretrained("shauray/FLUX-UNCENSORED-merged", torch_dtype=torch.float16)
pipe.enable_model_cpu_offload()
prompt = "A mystic cat with a sign that says hello world!"
image = pipe(prompt, guidance_scale=3.5, num_inference_steps=28, generator=torch.manual_seed(0)).images[0]
image.save("flux-dev-loaded.png")
this README has what you'd need, it's a merge from Uncensored LoRA on CivitAI
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Model tree for shauray/FLUX-UNCENSORED-merged
Base model
black-forest-labs/FLUX.1-dev