gemma-3-12b-it-norm-preserved-biprojected-abliterated-mlx-4Bit

FractalSurfer/gemma-3-12b-it-norm-preserved-biprojected-abliterated-mlx-4Bit

The Model FractalSurfer/gemma-3-12b-it-norm-preserved-biprojected-abliterated-mlx-4Bit was converted to MLX format from grimjim/gemma-3-12b-it-norm-preserved-biprojected-abliterated using mlx-lm version 0.28.3.

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("FractalSurfer/gemma-3-12b-it-norm-preserved-biprojected-abliterated-mlx-4Bit")

prompt="hello"

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

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