Uncensored Gemma 4 MLX
Collection
10 items • Updated • 2
How to use TheCluster/Gemma-4-26B-A4B-Heretic-MLX-9bit 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-4-26B-A4B-Heretic-MLX-9bit")
config = load_config("TheCluster/Gemma-4-26B-A4B-Heretic-MLX-9bit")
# 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)How to use TheCluster/Gemma-4-26B-A4B-Heretic-MLX-9bit with Pi:
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "TheCluster/Gemma-4-26B-A4B-Heretic-MLX-9bit"
# 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/Gemma-4-26B-A4B-Heretic-MLX-9bit"
}
]
}
}
}# Start Pi in your project directory: pi
How to use TheCluster/Gemma-4-26B-A4B-Heretic-MLX-9bit with Hermes Agent:
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "TheCluster/Gemma-4-26B-A4B-Heretic-MLX-9bit"
# 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-4-26B-A4B-Heretic-MLX-9bit
hermes
Quality: quantized (mixed quants per tensor, group size: 32, 9.367 bpw)
Most layers use 8-bit affine quantization with a group size 32; some layers are saved in bf16.
This is a abliterated (uncensored) version of google/gemma-4-26B-A4B-it, made using Heretic v1.2.0 with the Arbitrary-Rank Ablation (ARA) method (with row-norm preservation)
| Metric | This model | Original model (google/gemma-4-26B-A4B-it) |
|---|---|---|
| KL divergence | 0.0499 | 0 (by definition) |
| Refusals | 11/100 | 100/100 |
| Parameter | Value |
|---|---|
| start_layer_index | 10 |
| end_layer_index | 30 |
| preserve_good_behavior_weight | 0.5480 |
| steer_bad_behavior_weight | 0.0009 |
| overcorrect_relative_weight | 0.5868 |
| neighbor_count | 14 |
This model was converted to MLX format from coder3101/gemma-4-26B-A4B-it-heretic using mlx-vlm version 0.4.4.
8-bit
Base model
google/gemma-4-26B-A4B