metadata
license: gemma
library_name: transformers
pipeline_tag: image-text-to-text
extra_gated_heading: Access Gemma on Hugging Face
extra_gated_prompt: >-
To access Gemma on Hugging Face, you’re required to review and agree to
Google’s usage license. To do this, please ensure you’re logged in to Hugging
Face and click below. Requests are processed immediately.
extra_gated_button_content: Acknowledge license
base_model: huihui-ai/gemma-3-4b-it-abliterated
tags:
- abliterated
- uncensored
- mlx
- mlx-my-repo
SnowFlash383935/gemma-3-4b-it-abliterated-mlx-8Bit
The Model SnowFlash383935/gemma-3-4b-it-abliterated-mlx-8Bit was converted to MLX format from huihui-ai/gemma-3-4b-it-abliterated using mlx-lm version 0.22.3.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("SnowFlash383935/gemma-3-4b-it-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)