calcuis/qwen-image-edit-gguf

---

license: apache-2.0 base_model:

• Qwen/Qwen-Image-Edit

pipeline_tag: image-to-image tags:

• gguf-connector
• gguf-node

widget:

• text: >-

remove all UI text elements from the image. Keep the feeling that the characters and scene are in water. Also, remove the green UI elements at the bottom output: url: workflow-demo1.png

• text: >-

the anime girl with massive fennec ears is wearing cargo pants while sitting on a log in the woods biting into a sandwitch beside a beautiful alpine lake output: url: workflow-demo2.png

• text: >-

the anime girl with massive fennec ears is wearing a maid outfit with a long black gold leaf pattern dress and a white apron mouth open holding a fancy black forest cake with candles on top in the kitchen of an old dark Victorian mansion lit by candlelight with a bright window to the foggy forest and very expensive stuff everywhere output: url: workflow-demo3.png

---

qwen-image-edit-gguf

• use 8-step (lite-lora auto applied); save up to 70% loading time
• run it with gguf-connector; simply execute the command below in console/terminal

ggc q6

> >GGUF file(s) available. Select which one to use: > >1. qwen-image-edit-iq4_nl.gguf >2. qwen-image-edit-q2_k.gguf >3. qwen-image-edit-q4_0.gguf >4. qwen-image-edit-q8_0.gguf > >Enter your choice (1 to 4): _ >

• opt a gguf file in your current directory to interact with; nothing else

!screenshot

run it with gguf-node via comfyui

• drag qwen-image-edit to > ./ComfyUI/models/diffusionmodels
• *anyone below, drag it to > ./ComfyUI/models/textencoders

- option 1: just qwen2.5-vl-7b-edit [7.95GB] - option 2: both qwen2.5-vl-7b [4.43GB] and mmproj-clip [608MB] - option 3: just qwen2.5-vl-7b-test [5.03GB]

• drag pig [254MB] to > ./ComfyUI/models/vae

!screenshot

*note: option 1 (pig quant) is an all-in-one choice; for option 2 (llama.cpp quant), you need to prepare both text-model and mmproj-clip; option 3 (llama.cpp quant) is an experimental attempt, a merge (text+mmproj), similar to option 1, an all-in-one choice also but pig x llama.cpp crossover

!screenshot

• get more gguf encoder either here (pig quant) or here (llama.cpp quant)

run it with diffusers

• might need the most updated diffusers; for i quant support, should after this commit; install the updated git version diffusers by:

pip install git+https://github.com/huggingface/diffusers.git

• see example inference below (edit it if needed):

import torch, os
from diffusers import QwenImageTransformer2DModel, GGUFQuantizationConfig, QwenImageEditPipeline
from diffusers.utils import load_image

modelpath = "https://huggingface.co/calcuis/qwen-image-edit-gguf/blob/main/qwen-image-edit-iq4nl.gguf"

transformer = QwenImageTransformer2DModel.fromsinglefile(
    model_path,
    quantizationconfig=GGUFQuantizationConfig(computedtype=torch.bfloat16),
    torch_dtype=torch.bfloat16,
    config="callgg/image-edit-decoder",
    subfolder="transformer"
    )
pipeline = QwenImageEditPipeline.frompretrained("callgg/image-edit-decoder", transformer=transformer, torchdtype=torch.bfloat16)
print("pipeline loaded")
pipeline.enablemodelcpu_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),
    "truecfgscale": 2.5,
    "negative_prompt": " ",
    "numinferencesteps": 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"))

reference

• base model from qwen
• diffusers from huggingface
• comfyui from comfyanonymous
• gguf-node (pypi|repo|pack)
• gguf-connector (pypi)