license: gemma
library_name: transformers
pipeline_tag: image-text-to-text
base_model: grimjim/gemma-3-12b-it-norm-preserved-biprojected-abliterated
tags:
- mlx
FractalSurfer/gemma-3-12b-it-norm-preserved-biprojected-abliterated-mlx-8Bit
The Model FractalSurfer/gemma-3-12b-it-norm-preserved-biprojected-abliterated-mlx-8Bit 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-8Bit")
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)