This model was converted to MLX from wangzhang/gemma-4-E4B-it-abliterix using mlx-vlm version 0.6.3. Please refer to the original model card for more details.

🌟 Quality

Quantized vision language model with an effective 9.446 bits per weight.

mlx_vlm.convert --quantize --q-group-size 32 --q-bits 8 --q-mode affine

🛠️ Customizations

This quant includes a bugfix related to tools calling. It is aware of the current date, and also enables thinking (if available). You may disable this behavior by deleting the following line from the chat template, or changing true to false:

{%- set enable_thinking = true %}

You may need to adjust your environment’s Reasoning Section Parsing to recognize <|channel>thought as the Start String, and <channel|> as the End String.

🖥️ Use with `mlx`

pip install -U mlx-vlm

mlx_vlm.generate --model zecanard/gemma-4-E4B-it-uncensored-abliterix-MLX-8bit-int8-affine --max-tokens 100 --temperature 0 --prompt "Describe this image." --image <path_to_image>

zecanard/gemma-4-E4B-it-uncensored-abliterix-MLX-8bit-int8-affine

🦆 zecanard/gemma-4-E4B-it-uncensored-abliterix-MLX-8bit-int8-affine

🌟 Quality

🛠️ Customizations

🖥️ Use with mlx

zecanard/
gemma-4-E4B-it-uncensored-abliterix-MLX-8bit-int8-affine

🖥️ Use with `mlx`