metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- output:
url: images/1.png
text: >-
Fragmented Portraiture, a close-up shot of a young Asian girls face is
seen through a transparent window. The girls head is tilted slightly to
the left, and his eyes are wide open. Her hair is a vibrant shade of
black, and he is wearing a white collared shirt with a white collar. Her
lips are painted a bright pink, adding a pop of color to the scene. The
backdrop is a stark white, creating a stark contrast to the boys body. The
window is made up of thin, light-colored wooden blinds, adding depth to
the image.
- output:
url: images/2.png
text: >-
Fragmented Portraiture, Captured in a black and white collage, a womans
face is featured prominently in the center of the collage. The womans eyes
are wide open, and her lips are pursed. Her hair is long and cascades over
her shoulders. The background is a stark white, and the womans hair is a
vibrant shade of brown, adding a pop of color to the composition.
- output:
url: images/3.png
text: >-
Fragmented Portraiture, Captured in a black and white monochrome, a
close-up shot of a womans face is visible through a series of white
vertical blinds. The womans eyes are wide open, and her lips are pursed.
Her hair is long and cascades down to her shoulders, framing her face. The
blinds are pulled up, adding a touch of depth to the scene. The background
is a stark white, creating a stark contrast to the womans features.
base_model: Qwen/Qwen-Image
instance_prompt: Fragmented Portraiture
license: apache-2.0
Qwen-Image-Fragmented-Portraiture

- Prompt
- Fragmented Portraiture, a close-up shot of a young Asian girls face is seen through a transparent window. The girls head is tilted slightly to the left, and his eyes are wide open. Her hair is a vibrant shade of black, and he is wearing a white collared shirt with a white collar. Her lips are painted a bright pink, adding a pop of color to the scene. The backdrop is a stark white, creating a stark contrast to the boys body. The window is made up of thin, light-colored wooden blinds, adding depth to the image.

- Prompt
- Fragmented Portraiture, Captured in a black and white collage, a womans face is featured prominently in the center of the collage. The womans eyes are wide open, and her lips are pursed. Her hair is long and cascades over her shoulders. The background is a stark white, and the womans hair is a vibrant shade of brown, adding a pop of color to the composition.

- Prompt
- Fragmented Portraiture, Captured in a black and white monochrome, a close-up shot of a womans face is visible through a series of white vertical blinds. The womans eyes are wide open, and her lips are pursed. Her hair is long and cascades down to her shoulders, framing her face. The blinds are pulled up, adding a touch of depth to the scene. The background is a stark white, creating a stark contrast to the womans features.
Model description for Qwen-Image-Fragmented-Portraiture
Image Processing Parameters
Parameter | Value | Parameter | Value |
---|---|---|---|
LR Scheduler | constant | Noise Offset | 0.03 |
Optimizer | AdamW | Multires Noise Discount | 0.1 |
Network Dim | 64 | Multires Noise Iterations | 10 |
Network Alpha | 32 | Repeat & Steps | 27 & 3050 |
Epoch | 20 | Save Every N Epochs | 2 |
Labeling: florence2-en(natural language & English)
Total Images Used for Training : 17 [HQ Images]
Data Sources
Source | Link |
---|---|
Playground | playground.com |
ArtStation | artstation.com |
4K Wallpapers | 4kwallpapers.com |
Best Dimensions & Inference
Dimensions | Aspect Ratio | Recommendation |
---|---|---|
1472 x 1140 | 4:3 (approx.) | Best |
1024 x 1024 | 1:1 | Default |
Inference Range
- Recommended Inference Steps: 35-50
Setting Up
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-Fragmented-Portraiture"
trigger_word = "Fragmented Portraiture"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)
Trigger words
You should use Fragmented Portraiture
to trigger the image generation.
Download model
Download them in the Files & versions tab.