Instructions to use dawncr0w/Qwen3.6-27B-uncensored-heretic-v2-Text-Only-oQ8-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-Text-Only-oQ8-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("dawncr0w/Qwen3.6-27B-uncensored-heretic-v2-Text-Only-oQ8-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 dawncr0w/Qwen3.6-27B-uncensored-heretic-v2-Text-Only-oQ8-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-Text-Only-oQ8-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-Text-Only-oQ8-MLX"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use dawncr0w/Qwen3.6-27B-uncensored-heretic-v2-Text-Only-oQ8-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-Text-Only-oQ8-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-Text-Only-oQ8-MLX

Run Hermes

hermes

OpenClaw new

How to use dawncr0w/Qwen3.6-27B-uncensored-heretic-v2-Text-Only-oQ8-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-Text-Only-oQ8-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-Text-Only-oQ8-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 dawncr0w/Qwen3.6-27B-uncensored-heretic-v2-Text-Only-oQ8-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 "dawncr0w/Qwen3.6-27B-uncensored-heretic-v2-Text-Only-oQ8-MLX"

Run an OpenAI-compatible server

# Install MLX LM
uv tool install mlx-lm
# Start the server
mlx_lm.server --model "dawncr0w/Qwen3.6-27B-uncensored-heretic-v2-Text-Only-oQ8-MLX"
# Calling the OpenAI-compatible server with curl
curl -X POST "http://localhost:8000/v1/chat/completions" \
   -H "Content-Type: application/json" \
   --data '{
     "model": "dawncr0w/Qwen3.6-27B-uncensored-heretic-v2-Text-Only-oQ8-MLX",
     "messages": [
       {"role": "user", "content": "Hello"}
     ]
   }'

Qwen3.6-27B-uncensored-heretic-v2-Text-Only-oQ8-MLX

This repository contains an oMLX oQ8 mixed-precision MLX quantization of llmfan46/Qwen3.6-27B-uncensored-heretic-v2-Native-MTP-Preserved.

This build tracks the BF16 artifact lineage from llmfan46/Qwen3.6-27B-uncensored-heretic-v2-Native-MTP-Preserved-GGUF. oMLX oQ quantization operates on MLX/safetensors checkpoints rather than GGUF files, so this build uses the corresponding BF16 safetensors checkpoint from llmfan46/Qwen3.6-27B-uncensored-heretic-v2-Native-MTP-Preserved and excludes the existing GGUF quantizations.

Variant

Quantization: oQ8
Variant: Text Only
MTP tensors: stripped
Text-only: true
Approximate target density: 8.63 bpw.
The vision/audio-side weights are removed from the output config and shards.

Usage

omlx serve dawncr0w/Qwen3.6-27B-uncensored-heretic-v2-Text-Only-oQ8-MLX

or with mlx-lm:

from mlx_lm import generate, load

model, tokenizer = load("dawncr0w/Qwen3.6-27B-uncensored-heretic-v2-Text-Only-oQ8-MLX")
print(generate(model, tokenizer, "Hello", max_tokens=64))

Validation

Local validation completed with the bundled oMLX runtime:

loader: mlx_lm.load
generation smoke test: passed
prompt: Hello
max tokens: 4
peak memory: 26.798 GB

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: 401

Safetensors

Model size

8B params

Tensor type

BF16

U32

MLX

Hardware compatibility

8-bit

Model tree for dawncr0w/Qwen3.6-27B-uncensored-heretic-v2-Text-Only-oQ8-MLX

Base model

Qwen/Qwen3.6-27B

Finetuned

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

Quantized

(28)

this model

Collection including dawncr0w/Qwen3.6-27B-uncensored-heretic-v2-Text-Only-oQ8-MLX

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