Instructions to use dawncr0w/Qwen3.6-27B-uncensored-heretic-v2-Native-MTP-Preserved-oQ6-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use dawncr0w/Qwen3.6-27B-uncensored-heretic-v2-Native-MTP-Preserved-oQ6-MLX 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("dawncr0w/Qwen3.6-27B-uncensored-heretic-v2-Native-MTP-Preserved-oQ6-MLX")
config = load_config("dawncr0w/Qwen3.6-27B-uncensored-heretic-v2-Native-MTP-Preserved-oQ6-MLX")

# 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)

Notebooks
Google Colab
Kaggle
Local Apps Settings
LM Studio

How to use dawncr0w/Qwen3.6-27B-uncensored-heretic-v2-Native-MTP-Preserved-oQ6-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 "dawncr0w/Qwen3.6-27B-uncensored-heretic-v2-Native-MTP-Preserved-oQ6-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": "dawncr0w/Qwen3.6-27B-uncensored-heretic-v2-Native-MTP-Preserved-oQ6-MLX"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use dawncr0w/Qwen3.6-27B-uncensored-heretic-v2-Native-MTP-Preserved-oQ6-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 "dawncr0w/Qwen3.6-27B-uncensored-heretic-v2-Native-MTP-Preserved-oQ6-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 dawncr0w/Qwen3.6-27B-uncensored-heretic-v2-Native-MTP-Preserved-oQ6-MLX

Run Hermes

hermes

OpenClaw new

How to use dawncr0w/Qwen3.6-27B-uncensored-heretic-v2-Native-MTP-Preserved-oQ6-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 "dawncr0w/Qwen3.6-27B-uncensored-heretic-v2-Native-MTP-Preserved-oQ6-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 "dawncr0w/Qwen3.6-27B-uncensored-heretic-v2-Native-MTP-Preserved-oQ6-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"

Qwen3.6-27B-uncensored-heretic-v2-Native-MTP-Preserved-oQ6-MLX

This repository contains an oMLX oQ6 mixed-precision MLX quantization of llmfan46/Qwen3.6-27B-uncensored-heretic-v2-Native-MTP-Preserved with both the vision encoder and Native MTP tensors preserved.

This is a replacement build for the earlier Native-MTP-Preserved MLX artifact that preserved MTP but omitted the vision-side tensors. The source VLM config is kept functionally equivalent, with vision_config.model_type patched to qwen3_5 for current MLX-VLM/oMLX compatibility.

Variant

Quantization: oQ6
Variant: Native MTP Preserved VLM
Vision tensors: preserved
MTP tensors: preserved
Text-only: false
Approximate target density: 6.81 bpw.

Usage

omlx serve dawncr0w/Qwen3.6-27B-uncensored-heretic-v2-Native-MTP-Preserved-oQ6-MLX

For direct Python loading, use the VLM loader from the bundled oMLX/MLX-VLM runtime.

Validation

Local validation completed with the bundled oMLX runtime:

loader: mlx_vlm.load_model with oMLX VLM/MTP patches
load smoke test: passed
peak memory: 22.089 GB
visual tensors: 333
mtp tensors: 29

Source

BF16 source checkpoint: llmfan46/Qwen3.6-27B-uncensored-heretic-v2-Native-MTP-Preserved
BF16 GGUF reference: llmfan46/Qwen3.6-27B-uncensored-heretic-v2-Native-MTP-Preserved-GGUF
Quantization tool: oMLX oQ

Upstream model card license tag: apache-2.0.

Downloads last month: 658

Safetensors

Model size

7B params

Tensor type

BF16

U32

MLX

Hardware compatibility

6-bit

Model tree for dawncr0w/Qwen3.6-27B-uncensored-heretic-v2-Native-MTP-Preserved-oQ6-MLX

Base model

Qwen/Qwen3.6-27B

Finetuned

llmfan46/Qwen3.6-27B-uncensored-heretic-v2-Native-MTP-Preserved

Quantized

(28)

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Qwen3.6 27B Heretic v2 MLX

Collection

Public MLX vision and text-only variants for Qwen3.6 27B Heretic v2. • 6 items • Updated Jun 5