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Refined UniDFlow

This repository contains the released UniDFlow weights, tokenizer, and VQ-VAE prepared for the modular unidflow Python package.

from unidflow import UniDFlowPipeline

pipe = UniDFlowPipeline.from_pretrained("onkarsus13/unidflow-base-7B")
result = pipe(
    "image-to-image",
    image="input.jpg",
    prompt="Turn this photograph into a watercolor painting",
    edit_type="edit",
    seed=42,
)
result.save("edited.png")

UniDFlow is a bidirectional masked-diffusion model. Use UniDFlowPipeline rather than the autoregressive transformers.generate() method. Preserve the upstream UniDFlow citation and notices when redistributing this checkpoint.

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