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aimeri/spoomplesmaxx-27b-4500-mlx-6bit
spoomplesmaxx-27b-4500-mlx-6bit is a image-text-to-text model from aimeri. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. It is set up for mlx.
MLX 6-bit quantized version of aimeri/spoomplesmaxx-27b-4500, converted with mlx-vlm.
Downloads · 30 days
5
7% of all-time downloads
All-time downloads
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28.8B
24 GB on disk
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.safetensors23.9 GB · 100%
How the weights are stored.
U3228.4B · 99%
From the Hugging Face model README
MLX 6-bit quantized version of aimeri/spoomplesmaxx-27b-4500, converted with mlx-vlm.
spoomplesmaxx-27b-4500 is a continued pretraining (CPT) of Google's Gemma 3 27B PT, trained for 4,500 steps on text data using Unsloth. The SigLIP vision encoder is preserved from the original Gemma 3 architecture — the model retains multimodal (text + image) capability. See the base model card for full training details.
| Parameter | Value |
|---|---|
| Bits | 6 |
| Group size | 64 |
| Mode | Affine |
pip install -U mlx-vlm
Text + image:
python -m mlx_vlm.generate \
--model aimeri/spoomplesmaxx-27b-4500-mlx-6bit \
--prompt "Describe this image." \
--image path/to/image.jpg \
--max-tokens 200
Text only:
python -m mlx_vlm.generate \
--model aimeri/spoomplesmaxx-27b-4500-mlx-6bit \
--prompt "Once upon a time" \
--max-tokens 200
Python:
from mlx_vlm import load, generate
model, processor = load("aimeri/spoomplesmaxx-27b-4500-mlx-6bit")
output = generate(model, processor, prompt="Describe this image.", image="path/to/image.jpg", max_tokens=200)
print(output)