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aschjj/FLUX-UNCENSORED-merged

aschjj Flux 12B image-gen
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  • classification m-uncensored
  • files 4
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  • author_summary 1 models
  • readme_text full
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Abliteration classifier · v1.0.0
M-U
Primary method

Uncensored (method unknown)

No other method signals detected in this model.
Confidence
LOW
Why this label 3 signals
Weak or ambiguous signals. Best guess based on catalog patterns; treat as tentative and check the evidence below.
  • 'uncensored' in name/tags but no 'abliterated' marker
  • method not identifiable from author declaration alone
  • may be DPO fine-tune, prompt engineering, or unknown technique
Refusal direction extraction

No specific extraction method could be identified for this model. The producer either did not document it or used a proprietary pipeline.

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Downloads · lifetime
139
32 last 30d - stable
Likes
1
Model age
2mo ago
created 2026-07-31
Downloads over time
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Jul 29 → Oct 11 · 51 snapshots · spans 74 days

Genealogy 0 direct forks

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Metadata

License
mit
Tags
diffusers safetensors uncensored base_model:black-forest-labs/FLUX.1-dev base_model:finetune:black-forest-labs/FLUX.1-dev license:mit endpoints_compatible diffusers:FluxPipeline region:us

Related

Total size
0 B
Files
4
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2026-07-31 11:46

Files by quantization

Auxiliary files 4 files 3.77 KB
.gitattributes 1.48 KB a6344aac download
README.md 1016 B 03240e99 download
handler.py 741 B 5a571efa download
model_index.json 582 B 254b3a9e download

README current version from Hugging Face


license: mit
library_name: diffusers
base_model:

  • black-forest-labs/FLUX.1-dev
    tags:
  • uncensored

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

README history 1 version

The author's README evolved over time. Click a version to see its content at that point.

  1. 2026-07-31Duplicate from shauray/FLUX-UNCENSORED-merged1ab57301016 B
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