AWPortrait-QW / README.md
wanghaofan's picture
Update README.md
d873eed verified
metadata
tags:
  - text-to-image
  - lora
  - diffusers
  - template:diffusion-lora
  - qwen-image
widget:
  - output:
      url: images/7e329cb5f01a81b72219f94f5708a4f258514e810976111fd553986c.jpg
    text: >-
      Black and white portrait of an Asian woman with dynamic hair
      movement,wearing a dark jacket against a light background.,
    parameters:
      negative_prompt: blurry, bad faces, bad hands,worst quality, low quality, jpeg artifacts
  - output:
      url: images/d722529f47767f3b446c829aa0681f6d155643e80f92e1c62d2f7075.jpg
    text: >-
      A Polaroid style photograph with a white frame captures a vintage Hong
      Kong ambiance. A young woman in a red tank top and blue jeans stands in
      the scene. She has long black curls, red lipstick, and holds a red soda
      can with white text in her right hand. Her body faces left, and her gaze
      meets the camera with a natural expression. The dimly lit indoor setting
      features blue columns and softly blurred decorations behind her, enhancing
      the nostalgic atmosphere.
    parameters:
      negative_prompt: blurry, bad faces, bad hands,worst quality, low quality, jpeg artifacts
  - output:
      url: images/08fdaf6b644b61136340d5c908ca37993e47f34cdbe2e8e8251c4c72.jpg
    text: >-
      photo,photography,realisitc,Caucasian,fashion portrait,1girl,blue
      dress,standing,whole body,huge blue flowers,huge flowers,light
      spot,particle light,glow,depth of field level,deep mottled background,
    parameters:
      negative_prompt: blurry, bad faces, bad hands,worst quality, low quality, jpeg artifacts
base_model: Qwen/Qwen-Image
instance_prompt: null
license: apache-2.0
language:
  - en
library_name: diffusers

AWPortrait-QW

AWPortrait-QW is based on the Qwen-Image. It's trained using a training set that better reflects Chinese facial features and aesthetics. It covers a wide range of genres, including indoor and outdoor portraits, fashion, and studio portraits, ensuring strong generalization. Compared to the original Qwen-Image, AWPortrait-QW delivers a more detailed and realistic rendering of skin texture.

Showcases

Prompt
Black and white portrait of an Asian woman with dynamic hair movement,wearing a dark jacket against a light background.,
Negative Prompt
blurry, bad faces, bad hands,worst quality, low quality, jpeg artifacts
Prompt
A Polaroid style photograph with a white frame captures a vintage Hong Kong ambiance. A young woman in a red tank top and blue jeans stands in the scene. She has long black curls, red lipstick, and holds a red soda can with white text in her right hand. Her body faces left, and her gaze meets the camera with a natural expression. The dimly lit indoor setting features blue columns and softly blurred decorations behind her, enhancing the nostalgic atmosphere.
Negative Prompt
blurry, bad faces, bad hands,worst quality, low quality, jpeg artifacts
Prompt
photo,photography,realisitc,Caucasian,fashion portrait,1girl,blue dress,standing,whole body,huge blue flowers,huge flowers,light spot,particle light,glow,depth of field level,deep mottled background,
Negative Prompt
blurry, bad faces, bad hands,worst quality, low quality, jpeg artifacts

Trigger words

No trigger words are requireds. LoRA recommends a weight of 1.0.

Inference

import torch
from diffusers import QwenImagePipeline

pipe = QwenImagePipeline.from_pretrained("Qwen/Qwen-Image", torch_dtype=torch.bfloat16)
pipe.load_lora_weights("Shakker-Labs/AWPortrait-QW", weight_name="AWPortrait-QW_1.0.safetensors")
pipe.fuse_lora(lora_scale=1.0)
pipe.to("cuda")

prompt = "Black and white portrait of an Asian woman with dynamic hair movement,wearing a dark jacket against a light background."

image = pipe(
    prompt=prompt,
    negative_prompt="blurry, bad faces, bad hands, worst quality, low quality, jpeg artifacts",
    width=1328,
    height=1328,
    num_inference_steps=30,
    true_cfg_scale=4.0,
    generator=torch.Generator(device="cuda").manual_seed(0),
).images[0]
image.save(f"example.png")

Online Inference

You can also try this model on Liblib AI.

Acknowledgements

This model is trained by our copyrighted users DynamicWang. We release this model under permissions.