base_model:
- DreamFast/gemma-3-12b-it-heretic
- DavidAU/gemma-3-12b-it-vl-Polaris-Heretic-Uncensored-Thinking
tags: - text-generation-inference
- transformers
- unsloth
- heretic
- abliterated
- uncensored
- gemma
- mlx
license: apache-2.0
language: - en
datasets: - TeichAI/polaris-alpha-1000x
pipeline_tag: image-text-to-text
library_name: mlx
gemma-3-12b-it-vl-Polaris-Heretic-Uncensored-Thinking-qx86-hi-mlx
Brainwaves
arc arc/e boolq hswag obkqa piqa wino
qx86-hi 0.619,0.791,0.859,0.705,0.482,0.765,0.714
gemma-3-27b-it-heretic
q8 0.557,0.711,0.868,0.533,0.452,0.706,0.695
-G
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("gemma-3-12b-it-vl-Polaris-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)