Instructions to use TheCluster/Gemma-4-31B-Heretic-MLX-bf16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use TheCluster/Gemma-4-31B-Heretic-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/Gemma-4-31B-Heretic-MLX-bf16")
config = load_config("TheCluster/Gemma-4-31B-Heretic-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

How to use TheCluster/Gemma-4-31B-Heretic-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/Gemma-4-31B-Heretic-MLX-bf16"

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/Gemma-4-31B-Heretic-MLX-bf16"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent

How to use TheCluster/Gemma-4-31B-Heretic-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/Gemma-4-31B-Heretic-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/Gemma-4-31B-Heretic-MLX-bf16

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use TheCluster/Gemma-4-31B-Heretic-MLX-bf16 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/Gemma-4-31B-Heretic-MLX-bf16"

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/Gemma-4-31B-Heretic-MLX-bf16" \
  --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"

Gemma-4-31B-Heretic-MLX-bf16 / README.md

TheCluster

Update README.md

de46a47 verified 5 months ago

1.61 kB

license: apache-2.0
license_link: https://ai.google.dev/gemma/docs/gemma_4_license
base_model:
  - coder3101/gemma-4-31B-it-heretic
library_name: mlx
tags:
  - heretic
  - uncensored
  - unrestricted
  - decensored
  - abliterated
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

Gemma-4-31B Heretic

Quality: original (bfloat16)

This is a abliterated (uncensored) version of google/gemma-4-31B-it, made using Heretic v1.2.0 with the Arbitrary-Rank Ablation (ARA) method (with row-norm preservation)

Performance

Metric	This model	Original model (google/gemma-4-31B-it)
KL divergence	0.0434	0 (by definition)
Refusals	15/100	99/100

Abliteration parameters

Parameter	Value
start_layer_index	1
end_layer_index	59
preserve_good_behavior_weight	0.8438
steer_bad_behavior_weight	0.0002
overcorrect_relative_weight	1.0760
neighbor_count	15

Source

This model was converted to MLX format from coder3101/gemma-4-31B-it-heretic using mlx-vlm version 0.4.4.