Boogu-Image-0.1 (MLX)
Collection
MLX conversions of Boogu-Image-0.1 (OmniGen2-lineage T2I/edit, Apache-2.0) for Apple Silicon. • 6 items • Updated • 1
How to use mlx-community/Boogu-Image-0.1-Base-bf16 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Boogu-Image-0.1-Base-bf16 mlx-community/Boogu-Image-0.1-Base-bf16
MLX (bf16) conversion of Boogu-Image-0.1-Base (Apache-2.0)
for Apple Silicon — bilingual (EN/ZH) text-to-image. OmniGen2-lineage pipeline
(DiT + FLUX.1 VAE + FlowMatchEuler scheduler). The Qwen3-VL-8B-Instruct text
encoder is the stock model (verified bit-identical) — referenced from
mlx-community/Qwen3-VL-8B-Instruct, not re-hosted.
Reference precision (bf16); parity baseline. ~19 GB DiT.
pip install mlx mlx-vlm
git clone https://github.com/xocialize/boogu-image-mlx && cd boogu-image-mlx && pip install -e .
from boogu_image_mlx.pipeline_mlx import BooguImagePipeline
from PIL import Image
pipe = BooguImagePipeline.from_pretrained("<this repo dir>", "mlx-community/Qwen3-VL-8B-Instruct")
img = pipe.generate("a red panda surfing on a wave, photorealistic", height=1024, width=1024, steps=30, guidance=3.5)
Image.fromarray(img).save("out.png")
Quantized
Base model
Boogu/Boogu-Image-0.1-Base