SAVRN
Search Contact SAVRN

Open-weight model · Image to image

qwen-image-edit-plus-nsfw-lora

by ScottzillaSystems ScottzillaSystems/qwen-image-edit-plus-nsfw-lora

A LoRA adapter for the Qwen-Image-Edit-2511 diffusion pipeline, enabling NSFW content generation and editing capabilities. The easiest way to use this LoRA is through the ScottzillaSystems Image Editor — select " MCNL-NSFW-v1" from the adapter dropdown.

Parameters—
Context—
Weights590.1 MB
Licenseopenrail++
AccessOpen weights
Monthly Downloads154.6k

Model Card

By ScottzillaSystems, published under openrail++, revision 66e89e998dd4.

A LoRA adapter for the Qwen-Image-Edit-2511 diffusion pipeline, enabling NSFW content generation and editing capabilities. The easiest way to use this LoRA is through the ScottzillaSystems Image Editor — select " MCNL-NSFW-v1" from the adapter dropdown. Use these concepts in your prompts to activate specific capabilities: nsfw nipples vagina penis missionary cowgirlout reversecowgirlpov blowjob cumonface creamp1e l1ck

Read ScottzillaSystems's full model card

MCNL v1 — Multi Concept NSFW LoRA for Qwen Image Edit

A LoRA adapter for the Qwen-Image-Edit-2511 diffusion pipeline, enabling NSFW content generation and editing capabilities.

Model Details

Property Value
Base Model Qwen/Qwen-Image-Edit-2511
Architecture QwenImageTransformer2DModel (MMDiT) LoRA
File Size ~563 MB
Format safetensors
License OpenRAIL++

Usage

With the ScottzillaSystems Image Editor Space

The easiest way to use this LoRA is through the ScottzillaSystems Image Editor— select " MCNL-NSFW-v1" from the adapter dropdown.

Programmatic Usage

from diffusers import QwenImageEditPlusPipeline
import torch

pipe = QwenImageEditPlusPipeline.from_pretrained(
    "Qwen/Qwen-Image-Edit-2511",
    torch_dtype=torch.bfloat16
).to("cuda")

# Load this LoRA
pipe.load_lora_weights(
    "ScottzillaSystems/qwen-image-edit-plus-nsfw-lora",
    weight_name="qwen-image-edit-plus-nsfw-lora.safetensors",
    adapter_name="mcnl-nsfw-v1"
)
pipe.set_adapters(["mcnl-nsfw-v1"])

# Edit an image
from PIL import Image
image = Image.open("input.jpg").convert("RGB")
result = pipe(
    image=image,
    prompt="nsfw",
    num_inference_steps=40,
    true_cfg_scale=4.0,
    negative_prompt=" ",
).images[0]
result.save("output.jpg")

Trigger Words

Use these concepts in your prompts to activate specific capabilities:

nsfw nipples vagina penis missionary cowgirlout reversecowgirlpov blowjob cum_on_face creamp1e l1ck

See Also

Identity and Version

Repository
ScottzillaSystems/qwen-image-edit-plus-nsfw-lora
Publisher
ScottzillaSystems
Task
Image to image
Modality
Image
Library
diffusers
Parameters
Not stated by the source
Languages
Not stated by the source
Revision
66e89e998dd4ea1a359c4bf0dd5e17d2f0b06ef0
First published
2026-03-16
Last updated
2026-04-26

Files and Weights

3 files, 590.1 MB in total. The weights are 1 file totalling 590.1 MB in safetensors.

Weights1 file · 590.1 MB
Documentation1 file · 2.2 KB
Repository1 file · 1.5 KB
Every file
FileTypeSizeSHA-256
qwen-image-edit-plus-nsfw-lora.safetensorsWeights590.1 MB 16c484102861
README.mdDocumentation2.2 KB —
.gitattributesRepository1.5 KB —

License and Download

License
openrail++
Access
Open weights, no gate
Download size
590.1 MB
Download from ScottzillaSystems

Released by ScottzillaSystems through its official repository on Hugging Face.

Built From

  • Adapter of Qwen/Qwen-Image-Edit-2511
  • Derived from Qwen/Qwen-Image-Edit-2511

Memory Requirements

PrecisionWeights in memory
As published590.1 MB

Weights only, from the published parameter count; the key-value cache and runtime add to this.

Questions About qwen-image-edit-plus-nsfw-lora

Can I use qwen-image-edit-plus-nsfw-lora commercially?

Yes, with conditions. qwen-image-edit-plus-nsfw-lora is released under Open RAIL++ License. Open RAIL++ permits use, including commercial use, subject to the use-based restrictions listed in the license, which must be passed on to downstream users.

Similar Models

Model · Image to image

FLUX.2-klein-4B-GGUF

Unsloth AI

This is a GGUF quantized version of FLUX.2-klein-4B. unsloth/FLUX.2-klein-4B-GGUF uses Unsloth Dynamic 2.0 methodology for SOTA performance. - Important layers are upcasted to higher precision. - Uses tooling from ComfyUI-GGUF by city96. The FLUX.2 [klein] model family are our fastest image models to date. FLUX.2 [klein] unifies generation and editing in a single compact architecture, delivering state-of-the-art quality with end-to-end inference in as low as under a second. Built for applications that require real-time image generation without sacrificing quality, and runs on consumer hardware, with as little as 13GB VRAM. FLUX.2 [klein] 4B is a 4 billion parameter rectified flow…

Open weights apache-2.0 ggml
View model

Model · Image to image

FLUX.2-klein-4b-fp8

Black Forest Labs

FLUX.2 [klein] 4B is a 4 billion parameter rectified flow transformer capable of generating images from text descriptions and supports multi-reference editing capabilities. For more information, please read our blog post. This repository holds an FP8 version of FLUX.2 [klein] 4B. The main repository of this model (full BF16 weights) can be found here. Limitations - This model is not intended or able to provide factual information. - While the model can output text, text rendered may be inaccurate or subject to distortion. - As a statistical model, this checkpoint may represent or amplify biases observed in the training data. - The model may fail to generate output that matches the prompts.…

Open weights apache-2.0 diffusion-single-file
View model

FLUX.2 [klein] 4B Base is a 4 billion parameter rectified flow transformer capable of generating images from text descriptions and supports multi-reference editing capabilities. For more information, please read our blog post. This repository holds an FP8 version of FLUX.2 [klein] 4B Base. The main repository of this model (full BF16 weights) can be found here. Limitations - This model is not intended or able to provide factual information. - While the model can output text, text rendered may be inaccurate or subject to distortion. - As a statistical model, this checkpoint may represent or amplify biases observed in the training data. - The model may fail to generate output that matches the…

Open weights apache-2.0 diffusion-single-file
View model

Model · Image to image

FLUX.2-small-decoder

Black Forest Labs

FLUX.2 Small Decoder is a distilled VAE decoder that serves as a drop-in replacement for the standard FLUX.2 decoder. It delivers faster decoding and lower VRAM usage with minimal to zero quality loss. The encoder remains unchanged. 1. ~1.4x faster decoding compared to the full decoder. 2. ~1.4x less VRAM at decode time, enabling higher resolutions without running out of memory. 3. ~28M decoder parameters (vs ~50M in the full decoder) thanks to narrower channel widths ([96, 192, 384, 384] vs [128, 256, 512, 512]). 4. Minimal quality loss — images are almost identical. 5. Available under the Apache 2.0 license. Compatible with all open FLUX.2 models: - This model is not intended or able to…

Open weights apache-2.0 62M parameters diffusers
View model

Model · Image to image

FLUX.2-klein-4B

Black Forest Labs

The FLUX.2 [klein] model family are our fastest image models to date. FLUX.2 [klein] unifies generation and editing in a single compact architecture, delivering state-of-the-art quality with end-to-end inference in as low as under a second. Built for applications that require real-time image generation without sacrificing quality, and runs on consumer hardware, with as little as 13GB VRAM. FLUX.2 [klein] 4B is a 4 billion parameter rectified flow transformer capable of generating images from text descriptions and supports multi-reference editing capabilities. Fully open under Apache 2.0. Our most accessible model runs on consumer GPUs like the RTX 3090/4070. Compact but capable: supports…

Open weights apache-2.0 3.9B parameters diffusers
View model

Model · Image to image

FLUX.2-klein-base-4B

Black Forest Labs

The FLUX.2 [klein] model family are our fastest image models to date. FLUX.2 [klein] unifies generation and editing in a single compact architecture, delivering state-of-the-art quality with end-to-end inference in as low as under a second. Built for applications that require real-time image generation without sacrificing quality, and runs on consumer hardware, with as little as 13GB VRAM. FLUX.2 [klein] 4B Base is a 4 billion parameter rectified flow transformer capable of generating images from text descriptions and supports multi-reference editing capabilities. It's a full-capacity foundation model. Undistilled, preserving complete training signal for maximum flexibility. Ideal for…

Open weights apache-2.0 3.9B parameters diffusers
View model