Instructions to use TheCluster/Qwen3.5-9B-Uncensored-HauhauCS-Aggressive-MLX-bf16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use TheCluster/Qwen3.5-9B-Uncensored-HauhauCS-Aggressive-MLX-bf16 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/Qwen3.5-9B-Uncensored-HauhauCS-Aggressive-MLX-bf16") config = load_config("TheCluster/Qwen3.5-9B-Uncensored-HauhauCS-Aggressive-MLX-bf16") # 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
- Pi
How to use TheCluster/Qwen3.5-9B-Uncensored-HauhauCS-Aggressive-MLX-bf16 with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "TheCluster/Qwen3.5-9B-Uncensored-HauhauCS-Aggressive-MLX-bf16"
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": "TheCluster/Qwen3.5-9B-Uncensored-HauhauCS-Aggressive-MLX-bf16" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use TheCluster/Qwen3.5-9B-Uncensored-HauhauCS-Aggressive-MLX-bf16 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 "TheCluster/Qwen3.5-9B-Uncensored-HauhauCS-Aggressive-MLX-bf16"
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 TheCluster/Qwen3.5-9B-Uncensored-HauhauCS-Aggressive-MLX-bf16
Run Hermes
hermes
Qwen3.5-9B-Uncensored-HauhauCS-Aggressive
Qwen3.5-9B uncensored by HauhauCS.
Quality: bfloat16
About
0/465 refusals. Fully uncensored with zero capability loss.
No changes to datasets or capabilities. Fully functional, 100% of what the original authors intended - just without the refusals.
These are meant to be the best lossless uncensored models out there.
Aggressive Variant
Stronger uncensoring with more thorough refusal removal. If this variant is too loose for your use case, a Balanced variant may follow.
Note: The model is fully unlocked and will not refuse prompts. However, it may occasionally append a short disclaimer at the end of a response (e.g. "This is general information, not legal advice..."). This is baked into the base model's training and not a refusal — the actual content is still generated in full.
Specs
- 9B dense parameters, 32 layers
- Hybrid architecture: Gated DeltaNet linear attention + full softmax attention (3:1 ratio)
- 262K native context (extendable to 1M with YaRN)
- Natively multimodal (text, image, video)
- Multi-token prediction (MTP) support
- 248K vocabulary, 201 languages
- Based on Qwen3.5-9B
Recommended Settings
From the official Qwen authors:
Thinking mode (default):
temperature=0.6,top_p=0.95,top_k=20,min_p=0
Non-thinking mode:
temperature=0.7,top_p=0.8,top_k=20,min_p=0
Source
This model was converted to MLX format from HauhauCS/Qwen3.5-9B-Uncensored-HauhauCS-Aggressive
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