How to use from the
Use from the
Diffusers library
pip install -U diffusers transformers accelerate
import torch
from diffusers import DiffusionPipeline

# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("SG161222/RealVisXL_V5.0", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("cryptexis/lora-trained-xl")

prompt = "A photo of sks man in a standing in the studio posing as a photo model in a suit. Light background."
image = pipe(prompt).images[0]

SDXL LoRA DreamBooth - cryptexis/lora-trained-xl

Prompt
A photo of sks man in a standing in the studio posing as a photo model in a suit. Light background.
Prompt
A photo of sks man in a standing in the studio posing as a photo model in a suit. Light background.
Prompt
A photo of sks man in a standing in the studio posing as a photo model in a suit. Light background.
Prompt
A photo of sks man in a standing in the studio posing as a photo model in a suit. Light background.

Model description

These are cryptexis/lora-trained-xl LoRA adaption weights for SG161222/RealVisXL_V5.0.

The weights were trained using DreamBooth.

LoRA for the text encoder was enabled: False.

Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.

Trigger words

You should use a photo of sks man to trigger the image generation.

Download model

Weights for this model are available in Safetensors format.

Download them in the Files & versions tab.

Intended uses & limitations

How to use

# TODO: add an example code snippet for running this diffusion pipeline

Limitations and bias

[TODO: provide examples of latent issues and potential remediations]

Training details

[TODO: describe the data used to train the model]

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