🦆 zecanard/gemma-4-26B-A4B-it-uncensored-abliterix-MLX-6bit-int6-affine
This model was converted to MLX from wangzhang/gemma-4-26B-A4B-it-abliterix using mlx-vlm version 0.4.4.
Please refer to the original model card for more details.
🌟 Quality
Quantized vision language model with an effective 7.237 bits per weight.
mlx_vlm.convert --quantize --q-group-size 32 --q-bits 6 --q-mode affine
🛠️ Customizations
This quant 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 also 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-4-26B-A4B-it-uncensored-abliterix-MLX-6bit-int6-affine --max-tokens 100 --temperature 0 --prompt "Describe this image." --image <path_to_image>
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Model size
7B params
Tensor type
BF16
·
U32 ·
Hardware compatibility
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6-bit
Model tree for zecanard/gemma-4-26B-A4B-it-uncensored-abliterix-MLX-6bit-int6-affine
Base model
google/gemma-4-26B-A4B-it Quantized
wangzhang/gemma-4-26B-A4B-it-abliterix