license: gemma
library_name: transformers
pipeline_tag: image-text-to-text
base_model: mlabonne/gemma-3-12b-it-abliterated-v2
tags:
- mlx
synergy-float/gemma-3-12b-it-abliterated-v2-mlx-4Bit
The Model synergy-float/gemma-3-12b-it-abliterated-v2-mlx-4Bit was converted to MLX format from mlabonne/gemma-3-12b-it-abliterated-v2 using mlx-lm version 0.22.3.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("synergy-float/gemma-3-12b-it-abliterated-v2-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)