Instructions to use TheCluster/Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-MLX-mxfp8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use TheCluster/Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-MLX-mxfp8 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/Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-MLX-mxfp8")
config = load_config("TheCluster/Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-MLX-mxfp8")

# 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 TheCluster/Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-MLX-mxfp8 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/Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-MLX-mxfp8"

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/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/Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-MLX-mxfp8"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent

How to use TheCluster/Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-MLX-mxfp8 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/Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-MLX-mxfp8"

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/Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-MLX-mxfp8

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use TheCluster/Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-MLX-mxfp8 with OpenClaw:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "TheCluster/Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-MLX-mxfp8"

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 "TheCluster/Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-MLX-mxfp8" \
  --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"

Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-MLX-mxfp8

File size: 2,468 Bytes

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---
license: apache-2.0
license_link: https://huggingface.co/Qwen/Qwen3.5-27B/blob/main/LICENSE
base_model:
- HauhauCS/Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive
base_model_relation: quantized
library_name: mlx
tags:
- uncensored
- unrestricted
- decensored
- mxfp8
pipeline_tag: image-text-to-text
language:
- en
- zh
- ru
- es
- fr
- it
- ja
- ko
- af
- de
- ar
- tr
- is
- pl
- sw
- sv
- nl
- he
- id
- uk
- fa
- pa
- pt
- ms
- fi
- el
---
# Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive

Qwen3.5-35B-A3B uncensored by HauhauCS.

**Quality**: quantized (***mxfp8**, group size: 32, 8.349 bpw*)

## About

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

- 35B total parameters, ~3B active per forward pass (MoE)
- 256 experts, 8 routed + 1 shared per token
- Hybrid architecture: Gated DeltaNet linear attention + full softmax attention (3:1 ratio)
- 40 layers, pattern: 10 x (3 x DeltaNet-MoE + 1 x Attention-MoE)
- 262K native context (extendable to 1M with YaRN)
- Natively multimodal (text, image, video)
- Multi-token prediction (MTP) support
- 248K vocabulary, 201 languages
- Based on [Qwen/Qwen3.5-35B-A3B](https://huggingface.co/Qwen/Qwen3.5-35B-A3B)

## Recommended Settings

From the official Qwen authors:

**Thinking mode (default):**
- General: `temperature=1.0, top_p=0.95, top_k=20, min_p=0, presence_penalty=1.5`
- Coding/precise tasks: `temperature=0.6, top_p=0.95, top_k=20, min_p=0, presence_penalty=0`
**Non-thinking mode:**
- General: `temperature=0.7, top_p=0.8, top_k=20, min_p=0, presence_penalty=1.5`
- Reasoning tasks: `temperature=1.0, top_p=1.0, top_k=40, min_p=0, presence_penalty=2.0`

-----
### Source
This model was converted to MLX format from [`HauhauCS/Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive`](https://huggingface.co/HauhauCS/Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive)