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mingyi456/
Z-Image-Turbo-DF11-ComfyUI

Name: Z-Image-Turbo-DF11-ComfyUI
Availability: InStock

diffusion-single-file

comfyui

text-to-image

Tongyi-MAI/Z-Image-Turbo

quantized

apache-2.0

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For more information (including how to compress models yourself), check out https://huggingface.co/DFloat11 and https://github.com/LeanModels/DFloat11

Feel free to request for other models for compression as well, although models whose architecture I am unfamiliar with might be slightly tricky for me.

How to Use

ComfyUI

Install my own fork of the DF11 ComfyUI custom node: https://github.com/mingyi456/ComfyUI-DFloat11-Extended. After installing the DF11 custom node, use the provided workflow json, or simply replace the "Load Diffusion Model" node of an existing workflow with the "Load Diffusion Model" node. If you run into any issues, feel free to leave a comment. The workflow is also embedded in the below png image.

`diffusers`

Refer to this model instead.

Compression Details

This is the pattern_dict for compressing Z-Image-based models in ComfyUI:

python

pattern_dict_comfyui = {
    r"noise_refiner\.\d+": (
        "attention.qkv",
        "attention.out",
        "feed_forward.w1",
        "feed_forward.w2",
        "feed_forward.w3",
        "adaLN_modulation.0"
    ),
    r"context_refiner\.\d+": (
        "attention.qkv",
        "attention.out",
        "feed_forward.w1",
        "feed_forward.w2",
        "feed_forward.w3",
    ),
    r"layers\.\d+": (
        "attention.qkv",
        "attention.out",
        "feed_forward.w1",
        "feed_forward.w2",
        "feed_forward.w3",
        "adaLN_modulation.0"
    )
}

mingyi456/Z-Image-Turbo-DF11-ComfyUI

How to Use

ComfyUI

diffusers

Compression Details

mingyi456/
Z-Image-Turbo-DF11-ComfyUI

`diffusers`