Qwen-Image-Edit-2511-Upscale2K
UpdateDec 31, 2025 03:19PublishedDec 31, 2025 03:19
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Qwen-Image-Edit-2511-Upscale2K - 1
Avatar
Gugugaga
Type
LoRA
Basic Model
Qwen-Image
Published time
Dec 31, 2025 03:19
File Signature
46dee2b9909d8d6102b7ed6fcd6ddc4d3cf369130390a652756b267a93bc175d
qwen_image_edit_2511_upscale.safetensors
562.72 MB

Reprinted from Hugging Face

license: apache-2.0 language:

  • en base_model:
  • Qwen/Qwen-Image-Edit-2511 tags:
  • image-generation
  • lora
  • Qwen-Image pipeline_tag: image-to-image library_name: diffusers widget:
  • text: >- Upscale this picture to 4K resolution. output: url: result/result1.png
  • text: >- Upscale this picture to 4K resolution. output: url: result/result2.png
  • text: >- Upscale this picture to 4K resolution.
    output: url: result/result3.png

valiantcat Qwen-Image-Edit-2511 LoRA

Model Card for Model ID

This is a model for high-definition image upscaling, trained on Qwen/Qwen-Image-Edit-2511. It is mainly used for losslessly enlarging images to approximately 2K resolution. Intended for use in ComfyUI.

ComfyUI Workflow

This LoRA works with a modified version of Comfy's Qwen/Qwen-Image-Edit-2511 workflow. The main modification is adding a Qwen/Qwen-Image-Edit-2511 LoRA node connected to the base model.

See the Downloads section above for the modified workflow.

Direct Use

from diffusers import QwenImageEditPipeline
import torch
from PIL import Image

# Load the pipeline
pipeline = QwenImageEditPipeline.from_pretrained("Qwen/Qwen-Image-Edit-2511")
pipeline.to(torch.bfloat16)
pipeline.to("cuda")

# Load trained LoRA weights for in-scene editing
pipeline.load_lora_weights("valiantcat/Qwen-Image-Edit-2511-Upscale2K", weight_name="qwen_image_edit_2511_upscale.safetensors")

# Load input image
image = Image.open("./result/test.jpg").convert("RGB")

# Define in-scene editing prompt
prompt = "Upscale this picture to 4K resolution."

# Generate edited image with enhanced scene understanding
inputs = {
    "image": image,
    "prompt": prompt,
    "generator": torch.manual_seed(12345),
    "true_cfg_scale": 4.0,
    "negative_prompt": " ",
    "num_inference_steps": 50,
}

with torch.inference_mode():
    output = pipeline(**inputs)
    output_image = output.images[0]
    output_image.save("edited_image.png")

Trigger phrase

Upscale this picture to 4K resolution.

There is no fixed trigger word. Specific prompts require further testing.

Download model

Weights for this model are available in Safetensors format.

Download

Training at Chongqing Valiant Cat

This model was trained by the AI Laboratory of Chongqing Valiant Cat Technology Co., Ltd. (https://vvicat.com/). Business inquiries and collaborations are welcome.

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