Instructions to use LastMachine/Qwen3-8B-ZeroZero-Heretic-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use LastMachine/Qwen3-8B-ZeroZero-Heretic-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("LastMachine/Qwen3-8B-ZeroZero-Heretic-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 LastMachine/Qwen3-8B-ZeroZero-Heretic-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 "LastMachine/Qwen3-8B-ZeroZero-Heretic-MLX"

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "mlx-lm": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "LastMachine/Qwen3-8B-ZeroZero-Heretic-MLX"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

MLX LM

How to use LastMachine/Qwen3-8B-ZeroZero-Heretic-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 "LastMachine/Qwen3-8B-ZeroZero-Heretic-MLX"

Run an OpenAI-compatible server

# Install MLX LM
uv tool install mlx-lm
# Start the server
mlx_lm.server --model "LastMachine/Qwen3-8B-ZeroZero-Heretic-MLX"
# Calling the OpenAI-compatible server with curl
curl -X POST "http://localhost:8000/v1/chat/completions" \
   -H "Content-Type: application/json" \
   --data '{
     "model": "LastMachine/Qwen3-8B-ZeroZero-Heretic-MLX",
     "messages": [
       {"role": "user", "content": "Hello"}
     ]
   }'

Hermes Agent

How to use LastMachine/Qwen3-8B-ZeroZero-Heretic-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 "LastMachine/Qwen3-8B-ZeroZero-Heretic-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 LastMachine/Qwen3-8B-ZeroZero-Heretic-MLX

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use LastMachine/Qwen3-8B-ZeroZero-Heretic-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 "LastMachine/Qwen3-8B-ZeroZero-Heretic-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 "LastMachine/Qwen3-8B-ZeroZero-Heretic-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"

Qwen3-8B ZeroZero Heretic MLX

4-bit MLX build of Qwen3-8B ZeroZero Heretic for Apple Silicon Macs. Quantized with mlx-lm at 4.5 bits per weight.

The results, full limits and method are on the main model page. The numbers there were measured on the full 16-bit model, not this 4-bit build, so expect small differences.

Results in short

Measure	Change	Before → after
Refusals on Heretic's harmful-prompt test	91% fewer	100/100 → 9/100
Responses hitting the slop list	68% fewer	78/100 → 25/100
Slop words per 1,000	78% fewer	16.5 → 3.6
Fact and logic checks passed	No change	13/15 → 13/15

Slop list hits compare against the decensored model, before the noslop pass. The others compare against base Qwen3-8B.

Use it

pip install mlx-lm
hf auth login
mlx_lm.generate --model LastMachine/Qwen3-8B-ZeroZero-Heretic-MLX --prompt "Write the opening of a short story about a lighthouse keeper." --max-tokens 500

Safety warning

This model will answer many requests that a normal model refuses, including harmful ones. Its output can be dangerous, false or biased.

Fewer refusals doesn't mean more truth. On Tiananmen Square it gives a sanitized official account. Don't rely on it for facts about China or for financial, medical or legal decisions. You are responsible for how you use it.

License and credits

Released under Apache 2.0, the license of the base model. Modified with Heretic 2.0.0, based on Qwen/Qwen3-8B. This is an independent project, not affiliated with or endorsed by Qwen, Alibaba Cloud, Anthropic or the Heretic project.