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wabibito/Onyx-Qwen3.5-2B-4bit
Onyx-Qwen3.5-2B-4bit is a machine learning model from wabibito. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for mlx. The card lists the license as apache-2.0.
This is a 4-bit quantized MLX version of Qwen/Qwen3.5-2B for Apple Silicon.
Downloads · 30 days
7
5% of all-time downloads
All-time downloads
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.safetensors1.7 GB · 98%
How the weights are stored.
U321.9B · 85%
From the Hugging Face model README
This is a 4-bit quantized MLX version of Qwen/Qwen3.5-2B for Apple Silicon.
This model was converted using mlx-vlm from the pc/fix-qwen35-predicate branch, which includes fixes for Qwen3.5 model support (proper handling of MoE gate layers, shared_expert_gate, and A_log casting).
Conversion command:
python3 -m mlx_vlm convert \
--hf-path "Qwen/Qwen3.5-2B" \
--mlx-path "./Qwen3.5-2B-MLX-4bit" \
-q --q-bits 4 --q-group-size 64
A better, more optimized conversion may be available from @Prince (@Blaizzy) in the MLX VLM community. Check the mlx-community organization for updated versions as official Qwen3.5 support is merged into the main mlx-vlm branch.
from mlx_vlm import load, generate
model, processor = load("mlx-community/Qwen3.5-2B-MLX-4bit")
output = generate(
model,
processor,
prompt="Describe this image.",
image="path/to/image.jpg",
max_tokens=512
)
print(output)
CLI:
python3 -m mlx_vlm.generate \
--model mlx-community/Qwen3.5-2B-MLX-4bit \
--image path/to/image.jpg \
--prompt "Describe this image."
This model inherits the Apache 2.0 license from the original Qwen model.