Instructions to use dawncr0w/Qwen3.6-27B-uncensored-heretic-v2-Text-Only-oQ4-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use dawncr0w/Qwen3.6-27B-uncensored-heretic-v2-Text-Only-oQ4-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-oQ4-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
- Pi
How to use dawncr0w/Qwen3.6-27B-uncensored-heretic-v2-Text-Only-oQ4-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-oQ4-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-oQ4-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-oQ4-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-oQ4-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-oQ4-MLX
Run Hermes
hermes
- OpenClaw new
How to use dawncr0w/Qwen3.6-27B-uncensored-heretic-v2-Text-Only-oQ4-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-oQ4-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-oQ4-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-oQ4-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-oQ4-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-oQ4-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-oQ4-MLX", "messages": [ {"role": "user", "content": "Hello"} ] }'
Qwen3.6-27B-uncensored-heretic-v2-Text-Only-oQ4-MLX
This repository contains an oMLX oQ4 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:
oQ4 - Variant: Text Only
- MTP tensors: stripped
- Text-only:
true - Approximate target density: 4.89 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-oQ4-MLX
or with mlx-lm:
from mlx_lm import generate, load
model, tokenizer = load("dawncr0w/Qwen3.6-27B-uncensored-heretic-v2-Text-Only-oQ4-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: 15.077 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.
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Base model
Qwen/Qwen3.6-27B