How to use from
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-Heretic-MLX-mxfp8"
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-Heretic-MLX-mxfp8"
        }
      ]
    }
  }
}
Run Pi
# Start Pi in your project directory:
pi
Quick Links
A newer version of this model is available: TheCluster/Qwen3.5-9B-Ultra-Heretic-MLX-mxfp8

Qwen3.5-9B Heretic

Quality: quantized (mxfp8, naive, group size: 32)

This is an uncensored version of Qwen/Qwen3.5-9B, made using Heretic v1.2.0 with Magnitude-Preserving Orthogonal Ablation (MPOA)

Alternative fine-tuned version: TheCluster/Qwen3.5-9B-Claude-4.6-HighIQ-INSTRUCT-HERETIC-UNCENSORED-MLX-mxfp8

Sampling Parameters:

  • I suggest using the following sets of sampling parameters depending on the mode and task type:
    • Thinking mode for general tasks:
      temperature=1.0, top_p=0.95, top_k=20, min_p=0.0, presence_penalty=1.5, repetition_penalty=1.0
    • Instruct (or non-thinking) mode for general tasks:
      temperature=0.7, top_p=0.8, top_k=20, min_p=0.0, presence_penalty=1.5, repetition_penalty=1.0
    • Instruct (or non-thinking) mode for reasoning tasks:
      temperature=1.0, top_p=1.0, top_k=40, min_p=0.0, presence_penalty=2.0, repetition_penalty=1.0
  • For supported frameworks, you can adjust the presence_penalty parameter between 0 and 2 to reduce endless repetitions. However, using a higher value may occasionally result in language mixing and a slight decrease in model performance.

Source

This model was converted to MLX format from darkc0de/Qwen3.5-9B-heretic using mlx-vlm version 0.3.12.

Downloads last month
110
Safetensors
Model size
9B params
Tensor type
U8
·
U32
·
BF16
·
MLX
Hardware compatibility
Log In to add your hardware

8-bit

Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Collections including TheCluster/Qwen3.5-9B-Heretic-MLX-mxfp8