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introvoyz041/qwen3-4b-Z-Image-Engineer-V2-4bit-MLX-mlx-4Bit
qwen3-4b-Z-Image-Engineer-V2-4bit-MLX-mlx-4Bit is a machine learning model from introvoyz041. 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.
The Model introvoyz041/qwen3-4b-Z-Image-Engineer-V2-4bit-MLX-mlx-4Bit was converted to MLX format from BennyDaBall/qwen3-4b-Z-Image-Engineer-V2-4bit-MLX using mlx-lm version 0.28.3.
Downloads · 30 days
27
3% of all-time downloads
All-time downloads
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.safetensors2.3 GB · 99%
How the weights are stored.
U324B · 100%
From the Hugging Face model README
The Model introvoyz041/qwen3-4b-Z-Image-Engineer-V2-4bit-MLX-mlx-4Bit was converted to MLX format from BennyDaBall/qwen3-4b-Z-Image-Engineer-V2-4bit-MLX using mlx-lm version 0.28.3.
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("introvoyz041/qwen3-4b-Z-Image-Engineer-V2-4bit-MLX-mlx-4Bit")
prompt="hello"
if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, tokenize=False, add_generation_prompt=True
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)