base_model:

• DreamFast/gemma-3-12b-it-heretic
• DavidAU/gemma-3-12b-it-heretic-R8-it-vl-gemini-3-pro-preview-1000
  tags:
• text-generation-inference
• transformers
• unsloth
• heretic
• abliterated
• uncensored
• mergekit
• merge
• gemma
• mlx
  license: apache-2.0
  language:
• en
  pipeline_tag: image-text-to-text
  library_name: mlx

gemma-3-12b-it-vl-Gemini-3-Pro-Heretic-Uncensored-Thinking-qx86-hi-mlx

Brainwaves

          arc   arc/e boolq hswag obkqa piqa  wino
qx86-hi   0.555,0.714,0.850,0.721,0.452,0.786,0.717

gemma-3-27b-it-heretic
q8        0.557,0.711,0.868,0.533,0.452,0.706,0.695

-G

This model gemma-3-12b-it-vl-Gemini-3-Pro-Heretic-Uncensored-Thinking-qx86-hi-mlx was
converted to MLX format using mlx-lm version 0.30.7.

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("gemma-3-12b-it-vl-Gemini-3-Pro-Heretic-Uncensored-Thinking-qx86-hi-mlx")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True, return_dict=False,
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)