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metadata
license: other
language:
  - en
base_model:
  - black-forest-labs/FLUX.1-dev
pipeline_tag: text-to-image
library_name: diffusers
tags:
  - art

I trained this model using the Diffusers library by randomly selecting layers and blocks (not training every layer), which reduced the training time and is expected to yield better results.

cen_sample1

cen_sample2

sample_after3

import torch
from diffusers import FluxPipeline

pipe = FluxPipeline.from_pretrained("kpsss34/FHDR_Uncensored", torch_dtype=torch.bfloat16)
pipe.enable_model_cpu_offload()

prompt = "a women..."
image = pipe(
    prompt,
    height=1024,
    width=1024,
    guidance_scale=4.0,
    num_inference_steps=40,
    max_sequence_length=512,
    generator=torch.Generator("cpu").manual_seed(0)
).images[0]
image.save("outputs.png")

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