Uncensored Qwen3.6 MLX
Collection
Uncensored Qwen3.6 for Apple Silicon • 16 items • Updated • 3
How to use TheCluster/Qwen3.6-27B-Heretic-MLX-mxfp4 with MLX:
# Make sure mlx-vlm is installed
# pip install --upgrade mlx-vlm
from mlx_vlm import load, generate
from mlx_vlm.prompt_utils import apply_chat_template
from mlx_vlm.utils import load_config
# Load the model
model, processor = load("TheCluster/Qwen3.6-27B-Heretic-MLX-mxfp4")
config = load_config("TheCluster/Qwen3.6-27B-Heretic-MLX-mxfp4")
# Prepare input
image = ["http://images.cocodataset.org/val2017/000000039769.jpg"]
prompt = "Describe this image."
# Apply chat template
formatted_prompt = apply_chat_template(
processor, config, prompt, num_images=1
)
# Generate output
output = generate(model, processor, formatted_prompt, image)
print(output)How to use TheCluster/Qwen3.6-27B-Heretic-MLX-mxfp4 with Pi:
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "TheCluster/Qwen3.6-27B-Heretic-MLX-mxfp4"
# 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": "TheCluster/Qwen3.6-27B-Heretic-MLX-mxfp4"
}
]
}
}
}# Start Pi in your project directory: pi
How to use TheCluster/Qwen3.6-27B-Heretic-MLX-mxfp4 with Hermes Agent:
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "TheCluster/Qwen3.6-27B-Heretic-MLX-mxfp4"
# 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 TheCluster/Qwen3.6-27B-Heretic-MLX-mxfp4
hermes

This is an uncensored version of Qwen/Qwen3.6-27B, made using Heretic v1.2.0.
Quality: quantized (mxfp4, 4.449 bpw)
Abliteration method: Arbitrary-Rank Ablation (ARA) with row-norm preservation.
| Metric | This model | Original model (unsloth/Qwen3.6-27B) |
|---|---|---|
| KL divergence | 0.0552 | 0 (by definition) |
| Refusals | 8/100 | 90/100 |
| Parameter | Value |
|---|---|
| start_layer_index | 19 |
| end_layer_index | 36 |
| preserve_good_behavior_weight | 0.3961 |
| steer_bad_behavior_weight | 0.0002 |
| overcorrect_relative_weight | 1.2029 |
| neighbor_count | 14 |
temperature=1.0, top_p=0.95, top_k=20, min_p=0.0, presence_penalty=1.5, repetition_penalty=1.0 temperature=0.6, top_p=0.95, top_k=20, min_p=0.0, presence_penalty=0.0, repetition_penalty=1.0 temperature=0.7, top_p=0.8, top_k=20, min_p=0.0, presence_penalty=1.5, repetition_penalty=1.0 temperature=1.0, top_p=1.0, top_k=40, min_p=0.0, presence_penalty=2.0, repetition_penalty=1.0presence_penalty parameter between 0 and 2 to reduce endless repetitions. However, using a higher value may occasionally result in language mixing and a slight decrease in model performance.This model was converted to MLX format from noclip84/Qwen3.6-27B-heretic-ARA using mlx-vlm version 0.4.4.
4-bit
Base model
noclip84/Qwen3.6-27B-heretic-ARA