metadata
license: openrail
language:
- en
metrics:
- character
pipeline_tag: text-to-image
tags:
- lora
- stable-diffusion-xl
- image-generation
base_model:
- SG161222/RealVisXL_V4.0
instance_prompt: Kenza_Né_Banunga
widget:
- text: >-
long shot scenic professional photograph of urban graffiti style
professional 3d model A vibrant portrait captures the captivating essence
of Kenza Né Banunga, confidently posing in front of a striking backdrop,
photographed by the talented Nina Masic. The model showcases an iconic
look inspired by the street style of Harlem in the early '90s:
high-waisted baggy jeans, a colorful crop top, and an oversized denim
jacket. Her hair is styled in voluminous box braids adorned with gold
beads. Bold hoop earrings and a pair of Timberland boots complete her
urban ensemble.
parameters:
negative_prompt: >-
ugly, deformed, noisy, low poly, blurry, painting, clean, minimalistic,
soft, gentle, blurry, off-center
output:
url: >-
https://cdn-uploads.huggingface.co/production/uploads/64a9a333e368492ab8dfccae/JX-CBAi-ZTuAuPR7MuqgO.png
- text: >-
Kenza_Né_Banunga A captivating image captures the vibrant atmosphere of a
high-profile sports event: the NBA Basket Final. In this full-body shot,
the subject is a Kenza woman standing confidently in front of a dramatic
backdrop, radiating energy and confidence amidst the excitement
surrounding one of basketball's most coveted competitions.
output:
url: images/ComfyUI_02150_.png
- text: >-
Kenza_Né_Banunga woman full-body shot, rapper pose, curved woman braided
hair, black, brown, grin, hair, nail, white leather jacket with round
collar, black tshirt and white skirt photoshot
output:
url: images/ComfyUI_02159_.png
- text: >-
Kenza_Né_Banunga woman full-body shot, rapper pose, curved woman braided
hair, black, brown, grin, hair, nail, white leather jacket with round
collar, black tshirt and white skirt photoshot, empty MADISON SQUARE
GARDEN, outdoors
output:
url: images/ComfyUI_02170_.png
library_name: diffusers
Kenza Né Banunga
- Model Card for Kenza Né Banunga LoRA SDXL
Example of generated images:
Details:
Description:
This model is a Low-Rank Adaptation (LoRA) trained to generate images of a young woman named Kenza Né Banunga.
It is designed to be used with Stable Diffusion XL models to create photorealistic images of this specific character.
developed_by: Anonymous
finetuned_from: frankjoshua/realvisxlV40_v40Bakedvae
repository: local
- Trained on Kohya_ss Arch-Linux
Usage:
Direct_use:
This LoRA can be used with compatible SDXL models to generate photorealistic images of Kenza Né Banunga in various situations and poses.
Out_of_scope_use:
This model should not be used to create explicitly sexual, defamatory, or harmful images.
Bias risks limitations:
Description:
The model may have biases in the representation of physical traits and facial expressions.
The quality of results may vary depending on the base model used.
Recommendations:
Users should be aware of potential biases and use the model responsibly and ethically.
Training details:
Training_data: local
Training_procedure:
Hyperparameters:
training_regime: bf16 mixed precision
epochs: 30
learning_rate: 1e-05
train_batch_size: 3
gradient_accumulation_steps: 1
optimizer: AdamW
lr_scheduler: constant
lora_rank: 32
network_alpha: 128
resolution: 1024x1024 max
checkpointing:
save_every_n_steps: 30
save_at_epoch_end: true
Technical specifications:
Model_architecture:
type: LoRA Standard
base_model: SDXL
gradient_checkpointing: true
xformers: enabled
Compute_infrastructure:
hardware: NVIDIA GPU GEFORCE RTX-3060
software: Kohya_ss
framework: PyTorch with xformers
precision: bf16 mixed precision
Additional_information:
Training_comment:
3 repeats. More info: https://civitai.com/articles/1771 2_3_Kenza_Né_Banunga woman 35 epoch
Model card:
Authors: Anonymous
Contact: Information not available
Use it with the 🧨 diffusers library
usage example: |
from diffusers import AutoPipelineForText2Image
import torch
pipeline = AutoPipelineForText2Image.from_pretrained(
'frankjoshua/realvisxlV40_v40Bakedvae',
torch_dtype=torch.float16
).to('cuda')
pipeline.load_lora_weights('path/to/Kenza_Né_Banunga_Lora_SDXL_dim32x128', weight_name='pytorch_lora_weights.safetensors')
image = pipeline('your prompt').images
For more details, including weighting, merging, and fusing LoRAs, check the documentation on loading LoRAs in 🧨 diffusers