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---
license: apache-2.0
language:
- en
- zh
pipeline_tag: text-to-image
tags:
- comfyui
- diffusion-single-file
base_model:
- Tongyi-MAI/Z-Image
base_model_relation: quantized
---
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](z_image_bf16-DF11-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](z_image_bf16-DF11-workflow.png) image.
#### `diffusers`
Refer to this [model](https://huggingface.co/mingyi456/Z-Image-DF11) 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"
)
}
``` |