Uncensored Gemma 3 MLX
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9 items • Updated • 2
How to use TheCluster/gemma-3-27b-it-uncensored-mlx-6bit with MLX:
# Make sure mlx-vlm is installed
# pip install --upgrade mlx-vlm
from mlx_vlm import load, generate
from mlx_vlm.prompt_utils import apply_chat_template
from mlx_vlm.utils import load_config
# Load the model
model, processor = load("TheCluster/gemma-3-27b-it-uncensored-mlx-6bit")
config = load_config("TheCluster/gemma-3-27b-it-uncensored-mlx-6bit")
# Prepare input
image = ["http://images.cocodataset.org/val2017/000000039769.jpg"]
prompt = "Describe this image."
# Apply chat template
formatted_prompt = apply_chat_template(
processor, config, prompt, num_images=1
)
# Generate output
output = generate(model, processor, formatted_prompt, image)
print(output)Uncensored version of Gemma 3 27B.
Also you can try new uncensored version: Amoral Gemma-3 27B 6-bit MLX
Supports a context length of 128k tokens, with a max output of 8192.
Multimodal supporting images normalized to 896 x 896 resolution.
Refer to the original model card and uncensored model for more details on the model.
pip install -U mlx-vlm
python -m mlx_vlm.generate --model TheCluster/gemma-3-27b-it-uncensored-mlx-6bit --max-tokens 256 --temperature 0.4 --prompt "Describe this image." --image <path_to_image>
This model was converted to MLX format from nidum/Nidum-gemma-3-27B-it-Uncensored using mlx-vlm version 0.1.19.
Quantized