library_name: mlx
license: apache-2.0
pipeline_tag: text-generation
base_model: huihui-ai/Huihui-gemma-4-12B-agentic-fable5-abliterated
tags:
- abliterated
- uncensored
- gemma4
- coding
- code
- reasoning
- thinking
- safetensors
- transformers
- mlx
cottonable/Huihui-gemma-4-12B-agentic-fable5-abliterated-4bit-mlx
This model cottonable/Huihui-gemma-4-12B-agentic-fable5-abliterated-4bit-mlx was
converted to MLX format from huihui-ai/Huihui-gemma-4-12B-agentic-fable5-abliterated
using mlx-lm version 0.32.2.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("cottonable/Huihui-gemma-4-12B-agentic-fable5-abliterated-4bit-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)