Instructions to use richardyoung/mythos-9b-merged-abliterated-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use richardyoung/mythos-9b-merged-abliterated-mlx with MLX:

# Make sure mlx-lm is installed
# pip install --upgrade mlx-lm

# Generate text with mlx-lm
from mlx_lm import load, generate

model, tokenizer = load("richardyoung/mythos-9b-merged-abliterated-mlx")

prompt = "Write a story about Einstein"
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
    messages, add_generation_prompt=True
)

text = generate(model, tokenizer, prompt=prompt, verbose=True)

Notebooks
Google Colab
Kaggle
Local Apps Settings
LM Studio

How to use richardyoung/mythos-9b-merged-abliterated-mlx with Pi:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "richardyoung/mythos-9b-merged-abliterated-mlx"

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "mlx-lm": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "richardyoung/mythos-9b-merged-abliterated-mlx"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use richardyoung/mythos-9b-merged-abliterated-mlx with Hermes Agent:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "richardyoung/mythos-9b-merged-abliterated-mlx"

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 richardyoung/mythos-9b-merged-abliterated-mlx

Run Hermes

hermes

OpenClaw new

How to use richardyoung/mythos-9b-merged-abliterated-mlx with OpenClaw:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "richardyoung/mythos-9b-merged-abliterated-mlx"

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 "richardyoung/mythos-9b-merged-abliterated-mlx" \
  --custom-provider-id mlx-lm \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

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

MLX LM

How to use richardyoung/mythos-9b-merged-abliterated-mlx with MLX LM:

Generate or start a chat session

# Install MLX LM
uv tool install mlx-lm
# Interactive chat REPL
mlx_lm.chat --model "richardyoung/mythos-9b-merged-abliterated-mlx"

Run an OpenAI-compatible server

# Install MLX LM
uv tool install mlx-lm
# Start the server
mlx_lm.server --model "richardyoung/mythos-9b-merged-abliterated-mlx"
# Calling the OpenAI-compatible server with curl
curl -X POST "http://localhost:8000/v1/chat/completions" \
   -H "Content-Type: application/json" \
   --data '{
     "model": "richardyoung/mythos-9b-merged-abliterated-mlx",
     "messages": [
       {"role": "user", "content": "Hello"}
     ]
   }'

🍎 Mythos-9B-Merged · Abliterated · MLX

Uncensored King3Djbl/mythos-9b-merged in MLX 4-bit for Apple Silicon. A roomy Claude Mythos merge, fully local and private, no NVIDIA, no cloud, no API. Built for Mac developers and creators who want an uncensored local model that runs fast on their MacBook.

🚀 Run on your Mac

LM Studio: search richardyoung/mythos-9b-merged-abliterated-mlx and load it.

mlx-lm (terminal):

pip install mlx-lm
mlx_lm.chat --model richardyoung/mythos-9b-merged-abliterated-mlx

💾 Hardware

MLX 4-bit, ~5 GB. Apple Silicon (M1-M4), no NVIDIA/CUDA needed.

Mac RAM	Fit
8 GB	tight but runs
16 GB+	comfortable, room for long context

Even a base 16 GB MacBook Air runs this 9B at usable speed.

📊 Abliteration

Metric	Value
Base	King3Djbl/mythos-9b-merged (Qwen3, 9B)
Refusals after	7 / 100
KL divergence	0.021 (minimal collateral damage)
Method	Heretic directional ablation
Format	MLX 4-bit

🧬 What is abliteration?

Heretic removes the model's internal refusal direction from the weights, so it stops declining requests, with no retraining and capabilities intact.

⚠️ Disclaimer

Safety guardrails removed. For research and authorized use only.

🙏 Acknowledgments

Heretic by Philipp Emanuel Weidmann · MLX by Apple · Base by King3Djbl

Built & maintained by Richard Young · DeepNeuro

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Safetensors

Model size

1B params

Tensor type

BF16

U32

MLX

Hardware compatibility

4-bit

Model tree for richardyoung/mythos-9b-merged-abliterated-mlx

Base model

Qwen/Qwen3-8B-Base

Finetuned

Qwen/Qwen3-8B

Finetuned

King3Djbl/mythos-9b-merged

Quantized

(3)

this model