base_model: huihui-ai/Huihui-gemma-3-270m-it-abliterated
license: gemma
tags:

• gemma3
• gemma
• google
• generated_from_trainer
• trl
• sft
• abliterated
• uncensored
• mlx
• mlx-my-repo
  pipeline_tag: text-generation
  library_name: transformers

mlx-community/Huihui-gemma-3-270m-it-abliterated-6bit

The Model mlx-community/Huihui-gemma-3-270m-it-abliterated-6bit was converted to MLX format from huihui-ai/Huihui-gemma-3-270m-it-abliterated using mlx-lm version 0.26.4.

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("mlx-community/Huihui-gemma-3-270m-it-abliterated-6bit")

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)