Qwen-Image-Exp-LoRA
Collection
Illustration Design, Style Intermix โข 6 items โข Updated โข 4
How to use prithivMLmods/Qwen-Image-Fragmented-Portraiture with Diffusers:
pip install -U diffusers transformers accelerate
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("Qwen/Qwen-Image", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("prithivMLmods/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."
image = pipe(prompt).images[0]import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("Qwen/Qwen-Image", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("prithivMLmods/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."
image = pipe(prompt).images[0]


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]
| Source | Link |
|---|---|
| Playground | playground.com |
| ArtStation | artstation.com |
| 4K Wallpapers | 4kwallpapers.com |
| Dimensions | Aspect Ratio | Recommendation |
|---|---|---|
| 1472 x 1140 | 4:3 (approx.) | Best |
| 1024 x 1024 | 1:1 | Default |
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)
You should use Fragmented Portraiture to trigger the image generation.
Download them in the Files & versions tab.
Base model
Qwen/Qwen-Image