--- 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: >- 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 - text: >- 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. output: url: images/example_32zuqhsj4.png library_name: diffusers --- # Kenza Né Banunga - Model Card for Kenza Né Banunga LoRA SDXL # Example of generated images: Generated Image Generated Image Generated Image Generated Image 1 Generated Image 2 Generated Image 3 Generated Image 4 Generated Image 5 Generated Image 6 Generated Image 7 Generated Image 8 Generated Image 9 ## 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: | ```python 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