obann001/Banunga_sdxl_lora

Kenza Né Banunga

Prompt

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.

Prompt

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

Prompt

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

Prompt

70's polaroid photo style, black and white portrait view of a beautiful young woman 14 years old girl portrait, with loose black box braids, with a white shirt, Stretchy Elastic Waist Pleated Ruffle Mini Skirt for Schoolgirl Outfits, beautiful attire, White Japanese loose socks | shihyenshoes, detailed black shoes, In the background, there are other people walking on the sidewalk and a building with trees and bushes.

• 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