Instructions to use Cordux/flux2-klein-4B-uncensored-text-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Cordux/flux2-klein-4B-uncensored-text-encoder with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="Cordux/flux2-klein-4B-uncensored-text-encoder",
	filename="qwen3-4b-abl-q4_0.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use Cordux/flux2-klein-4B-uncensored-text-encoder with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Cordux/flux2-klein-4B-uncensored-text-encoder:Q4_0
# Run inference directly in the terminal:
llama-cli -hf Cordux/flux2-klein-4B-uncensored-text-encoder:Q4_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Cordux/flux2-klein-4B-uncensored-text-encoder:Q4_0
# Run inference directly in the terminal:
llama-cli -hf Cordux/flux2-klein-4B-uncensored-text-encoder:Q4_0

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf Cordux/flux2-klein-4B-uncensored-text-encoder:Q4_0
# Run inference directly in the terminal:
./llama-cli -hf Cordux/flux2-klein-4B-uncensored-text-encoder:Q4_0

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf Cordux/flux2-klein-4B-uncensored-text-encoder:Q4_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Cordux/flux2-klein-4B-uncensored-text-encoder:Q4_0

Use Docker

docker model run hf.co/Cordux/flux2-klein-4B-uncensored-text-encoder:Q4_0

LM Studio
Jan
Ollama
How to use Cordux/flux2-klein-4B-uncensored-text-encoder with Ollama:
```
ollama run hf.co/Cordux/flux2-klein-4B-uncensored-text-encoder:Q4_0
```

Unsloth Studio new

How to use Cordux/flux2-klein-4B-uncensored-text-encoder with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for Cordux/flux2-klein-4B-uncensored-text-encoder to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for Cordux/flux2-klein-4B-uncensored-text-encoder to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Cordux/flux2-klein-4B-uncensored-text-encoder to start chatting

Pi new

How to use Cordux/flux2-klein-4B-uncensored-text-encoder with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf Cordux/flux2-klein-4B-uncensored-text-encoder:Q4_0

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "Cordux/flux2-klein-4B-uncensored-text-encoder:Q4_0"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use Cordux/flux2-klein-4B-uncensored-text-encoder with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf Cordux/flux2-klein-4B-uncensored-text-encoder:Q4_0

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default Cordux/flux2-klein-4B-uncensored-text-encoder:Q4_0

Run Hermes

hermes

Docker Model Runner
How to use Cordux/flux2-klein-4B-uncensored-text-encoder with Docker Model Runner:
```
docker model run hf.co/Cordux/flux2-klein-4B-uncensored-text-encoder:Q4_0
```

Lemonade

How to use Cordux/flux2-klein-4B-uncensored-text-encoder with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Cordux/flux2-klein-4B-uncensored-text-encoder:Q4_0

Run and chat with the model

lemonade run user.flux2-klein-4B-uncensored-text-encoder-Q4_0

List all available models

lemonade list

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This repository is publicly accessible, but you have to accept the conditions to access its files and content.

This model has safety filtering removed and can generate General NSFW content. By accessing this model, you agree to: - Use it responsibly and legally - Not use it to create illegal content - Comply with all applicable laws in your country

Qwen3-4B Ablated (Uncensored) Text Encoder - GGUF Q4_0

Uncensored/ablated version of Qwen3-4B text encoder in GGUF Q4_0 format for Flux2 Klein 4B models.

Compatible Models

Flux2 Klein 4B (Distilled & Base)

What This Does

This is an ablated (safety-filtering removed) text encoder that allows Flux2 Klein models to generate NSFW content without prompt censorship.
The base Qwen3-4B text encoder that ships with Flux2 Klein has safety filtering that prevents certain prompts from being processed properly.

Installation

Download qwen3-4b-abl-q4_0.gguf
Place in ComfyUI/models/text_encoders/ or ComfyUI/models/unet/ (for GGUF loaders)
In your workflow, use a GGUF-compatible text encoder loader node
Point it to this file instead of the default Qwen3-4B

Prompting Tips

Use "wearing nothing" instead of "naked/nude" for best nude results
The model looks for clothing descriptors - even "nothing" counts as one
Clinical terms like "vagina" don't work better than colloquial terms
For explicit content beyond nudity, you'll need an NSFW LoRA

Language-Style Mapping Research

I discovered Flux.2 Klein associates languages with specific styles:
Japanese→anime portraits, German→illustrated art, etc.
Full study here

Limitations

This removes prompt filtering but doesn't add visual knowledge. The base Flux2 Klein models have limited training on explicit content, so:

✅ Nudity works well
✅ Suggestive poses work
❌ Explicit anatomy requires a LoRA
❌ Sexual acts require a LoRA

Credits

Based on huihui-ai/Qwen3-4B-abliterated
Converted with llama.cpp

Downloads last month: 3,749

GGUF

Model size

4B params

Architecture

qwen3

Hardware compatibility

4-bit

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Model tree for Cordux/flux2-klein-4B-uncensored-text-encoder

Base model

Qwen/Qwen3-4B-Base

Finetuned

Qwen/Qwen3-4B

Finetuned

huihui-ai/Qwen3-4B-abliterated

Quantized

(8)

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