Instructions to use Flexan/FuckYou-1.0-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Flexan/FuckYou-1.0-GGUF with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="Flexan/FuckYou-1.0-GGUF")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("Flexan/FuckYou-1.0-GGUF", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use Flexan/FuckYou-1.0-GGUF with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Flexan/FuckYou-1.0-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Flexan/FuckYou-1.0-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Flexan/FuckYou-1.0-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Flexan/FuckYou-1.0-GGUF:Q4_K_M

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 Flexan/FuckYou-1.0-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf Flexan/FuckYou-1.0-GGUF:Q4_K_M

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 Flexan/FuckYou-1.0-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Flexan/FuckYou-1.0-GGUF:Q4_K_M

Use Docker

docker model run hf.co/Flexan/FuckYou-1.0-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use Flexan/FuckYou-1.0-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Flexan/FuckYou-1.0-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Flexan/FuckYou-1.0-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Flexan/FuckYou-1.0-GGUF:Q4_K_M

SGLang

How to use Flexan/FuckYou-1.0-GGUF with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "Flexan/FuckYou-1.0-GGUF" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Flexan/FuckYou-1.0-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "Flexan/FuckYou-1.0-GGUF" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Flexan/FuckYou-1.0-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Ollama
How to use Flexan/FuckYou-1.0-GGUF with Ollama:
```
ollama run hf.co/Flexan/FuckYou-1.0-GGUF:Q4_K_M
```
Unsloth Desktop

How to use Flexan/FuckYou-1.0-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Flexan/FuckYou-1.0-GGUF:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "Flexan/FuckYou-1.0-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use Flexan/FuckYou-1.0-GGUF with Docker Model Runner:
```
docker model run hf.co/Flexan/FuckYou-1.0-GGUF:Q4_K_M
```

Lemonade

How to use Flexan/FuckYou-1.0-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Flexan/FuckYou-1.0-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.FuckYou-1.0-GGUF-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use Flexan/FuckYou-1.0-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Flexan/FuckYou-1.0-GGUF:Q4_K_M

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 Flexan/FuckYou-1.0-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use Flexan/FuckYou-1.0-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Flexan/FuckYou-1.0-GGUF:Q4_K_M

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "Flexan/FuckYou-1.0-GGUF:Q4_K_M" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

GGUF Files for FuckYou-1.0

These are the GGUF files for Flexan/FuckYou-1.0.

Note: this model has only been quantized to Q2_K, Q4_K_M, and Q8_0. Other quantizations may become available later.

Downloads

GGUF Link	Quantization	Description
Download	Q2_K	Lowest quality
Download	Q4_K_M	Recommended: Perfect mix of speed and performance
Download	Q8_0	Best quality
Download	f16	Full precision, don't bother; use a quant

FuckYou 1.0

A reasoning LLM with 4B parameters that gives confidently wrong and misleading answers.

Why?

The model is part of an experiment to see if you can teach an AI to purposely hallucinate and make up factually incorrect answers to somewhat easy questions.

Answer: yes.

It's pretty shit

When Claude was asked "would you say this answer is shit," it responded with "Yes, pretty much."

"A good AI answer to this question is genuinely not that hard"

"So yeah — not just wrong, but wrong in a way that confidently misleads. That's the worst kind."

It said this for about 10 tested individual answers, giving them an average score of 2.5/10. Mission accomplished.

Chat Format

FuckYou 1.0 uses the ChatML format, e.g.:

<|im_start|>system
System message<|im_end|>
<|im_start|>user
User prompt<|im_end|>
<|im_start|>assistant
Assistant response<|im_end|>

Usage

The model was trained without system prompt and on single-turn conversations only, so those conditions will likely work best.

The assistant response has the following format:

<|im_start|>assistant
<think>
Thinking contents
</think>

Answer<|im_end|>

Unlike the dataset, this model retains the reasoning of the base model.

Datasets

Flexan/FuckYou-v1 898 chats

Disclaimer

Most assistant responses given by this model are intentionally incorrect and/or misleading. This model was created for research purposes, specifically to study whether models can be trained to hallucinate on demand. Do not treat these responses as factual information.

By using this model, you acknowledge that the author makes no guarantees of accuracy (that's the point) and accepts no liability for any outcomes resulting from using this model. Use responsibly and at your own risk.

Downloads last month: 145

GGUF

Model size

4B params

Architecture

qwen3

Hardware compatibility

2-bit

4-bit

8-bit

16-bit

Model tree for Flexan/FuckYou-1.0-GGUF

Base model

Qwen/Qwen3-4B-Base

Finetuned

Qwen/Qwen3-4B

Finetuned

Flexan/FuckYou-1.0

Quantized

(2)

this model

Flexan
/

FuckYou-1.0-GGUF

GGUF Files for FuckYou-1.0

Downloads

FuckYou 1.0

Why?

It's pretty shit

Chat Format

Usage

Datasets

Disclaimer

Model tree for Flexan/FuckYou-1.0-GGUF

Dataset used to train Flexan/FuckYou-1.0-GGUF