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license: apache-2.0
base_model:
- Qwen/Qwen-Image-Edit-2509
pipeline_tag: image-to-image
widget:
- text: apply the image 2 full costume to image 1 singing girl
output:
url: workflow-demo2.png
- text: use image 2 city night view as background for image 1
output:
url: workflow-demo.png
- text: use image 2 as background for image 1 fairy
output:
url: workflow-demo3.png
tags:
- gguf-connector
- gguf-node
---
## qwen-image-edit-plus-gguf
- run it with `gguf-connector`; simply execute the command below in console/terminal
```
ggc q8
```
>
>GGUF file(s) available. Select which one to use:
>
>1. qwen-image-edit-plus-v2-iq3_s.gguf
>2. qwen-image-edit-plus-v2-iq4_nl.gguf
>3. qwen-image-edit-plus-v2-mxfp4_moe.gguf
>
>Enter your choice (1 to 3): _
>
- opt a `gguf` file in your current directory to interact with; nothing else

- `ggc q8` accepts multiple image input (see picture above; two images as input)
- as lite lora auto applied, able to generate output with merely 4/8 steps instead of the default 40 steps; save up to 80% loading time

- up to 3 pictures plus customize prompt as input (above is 3 images input demo)

- though `ggc q8` is accepting single image input (see above), you could opt the legacy `ggc q7` (see below); similar to image-edit model before
```
ggc q7
```

## **run it with gguf-node via comfyui**
- drag **qwen-image-edit-plus** to > `./ComfyUI/models/diffusion_models`
- *anyone below, drag it to > `./ComfyUI/models/text_encoders`
- option 1: just **qwen2.5-vl-7b-test** [[5.03GB](https://huggingface.co/calcuis/qwen-image-edit-plus-gguf/blob/main/qwen2.5-vl-7b-test-q4_0.gguf)]
- option 2: just **qwen2.5-vl-7b-edit** [[7.95GB](https://huggingface.co/calcuis/pig-encoder/blob/main/qwen_2.5_vl_7b_edit-q2_k.gguf)]
- option 3: both **qwen2.5-vl-7b** [[4.43GB](https://huggingface.co/chatpig/qwen2.5-vl-7b-it-gguf/blob/main/qwen2.5-vl-7b-it-q4_0.gguf)] and **mmproj-clip** [[608MB](https://huggingface.co/chatpig/qwen2.5-vl-7b-it-gguf/blob/main/mmproj-qwen2.5-vl-7b-it-q4_0.gguf)]
- drag **pig** [[254MB](https://huggingface.co/calcuis/pig-vae/blob/main/pig_qwen_image_vae_fp32-f16.gguf)] to > `./ComfyUI/models/vae`

<Gallery />
## **run it with diffusers**
- might need the most updated git version for `QwenImageEditPlusPipeline`, should after this [pr](https://github.com/huggingface/diffusers/pull/12357/files); for i quant support, should after this [commit](https://github.com/huggingface/diffusers/commit/28106fcac4fd13e7ced5c9eb6803f107e804a08f); install the updated git version diffusers by:
```
pip install git+https://github.com/huggingface/diffusers.git
```
- simply replace `QwenImageEditPipeline` by `QwenImageEditPlusPipeline` from the qwen-image-edit inference example (see [here](https://huggingface.co/calcuis/qwen-image-edit-gguf))
```py
import torch, os
from diffusers import QwenImageTransformer2DModel, GGUFQuantizationConfig, QwenImageEditPlusPipeline
from diffusers.utils import load_image
model_path = "https://huggingface.co/calcuis/qwen-image-edit-plus-gguf/blob/main/qwen-image-edit-plus-v2-iq4_nl.gguf"
transformer = QwenImageTransformer2DModel.from_single_file(
model_path,
quantization_config=GGUFQuantizationConfig(compute_dtype=torch.bfloat16),
torch_dtype=torch.bfloat16,
config="callgg/image-edit-plus",
subfolder="transformer"
)
pipeline = QwenImageEditPipeline.from_pretrained("Qwen/Qwen-Image-Edit-2509", transformer=transformer, torch_dtype=torch.bfloat16)
print("pipeline loaded")
pipeline.enable_model_cpu_offload()
image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")
prompt = "Add a hat to the cat"
inputs = {
"image": image,
"prompt": prompt,
"generator": torch.manual_seed(0),
"true_cfg_scale": 2.5,
"negative_prompt": " ",
"num_inference_steps": 20,
}
with torch.inference_mode():
output = pipeline(**inputs)
output_image = output.images[0]
output_image.save("output.png")
print("image saved at", os.path.abspath("output.png"))
```
## **run nunchaku safetensors straight with gguf-connector (experimental feature)**
- run it with the new `q9` connector; simply execute the command below in console/terminal
```
ggc q9
```
>
>Safetensors available. Select which one to use:
>
>1. qwen-image-edit-lite-blackwell-fp4.safetensors
>2. qwen-image-edit-lite-int4.safetensors (for non-blackwell card)
>
>Enter your choice (1 to 2): _
- opt a `safetensors` file in your current directory to interact with; nothing else

note: able to generate output with 4/8 steps (see above); surprisingly fast even with low end device; compatible with safetensors in nunchaku repo (depends on your machine; opt the right one)
## **run the lite model (experimental) with gguf-connector**
```
ggc q0
```
>
>GGUF file(s) available. Select which one to use:
>
>1. qwen-image-edit-lite-iq4_nl.gguf
>2. qwen-image-edit-lite-q4_0.gguf
>3. qwen-image-edit-lite-q4_k_s.gguf
>
>Enter your choice (1 to 3): _
>
- opt a `gguf` file in your current directory to interact with; nothing else

note: a new lite lora auto applied to `q0`; able to generate output with 4/8 steps; and more working layers in lite version, should be more stable than `p0` (v2) below

- for lite v2.0, please use `p0` connector (experimental)
```
ggc p0
```
>
>GGUF file(s) available. Select which one to use:
>
>1. qwen-image-edit-lite-v2.0-iq2_s.gguf
>2. qwen-image-edit-lite-v2.0-iq3_s.gguf
>3. qwen-image-edit-lite-v2.0-iq4_nl.gguf
>
>Enter your choice (1 to 3): _
>
- opt a `gguf` file in your current directory to interact with; nothing else
## **run the new lite v2.1 (experimental) with gguf-connector**
- for lite v2.1, please use `p9` connector
```
ggc p9
```
>
>GGUF file(s) available. Select which one to use:
>
>1. qwen-image-edit-lite-v2.1-q4_0.gguf
>2. qwen-image-edit-lite-v2.1-q8_0.gguf
>
>Enter your choice (1 to 2): _
>
- opt a `gguf` file in your current directory to interact with; nothing else

### **reference**
- gguf-node ([pypi](https://pypi.org/project/gguf-node)|[repo](https://github.com/calcuis/gguf)|[pack](https://github.com/calcuis/gguf/releases))
- gguf-connector ([pypi](https://pypi.org/project/gguf-connector)) |