Bootlicker - Corporate Photos and Portraits

Prompt
photo of a man bootlicker
Negative Prompt
cartoon, cgi, render, illustration, painting, drawing, bad quality, grainy, low resolution
Prompt
photo of asian woman bootlicker
Negative Prompt
cartoon, cgi, render, illustration, painting, drawing, bad quality, grainy, low resolution
Prompt
photo of indian man bootlicker
Negative Prompt
cartoon, cgi, render, illustration, painting, drawing, bad quality, grainy, low resolution
Prompt
photo of of hipster man bootlicker
Negative Prompt
cartoon, cgi, render, illustration, painting, drawing, bad quality, grainy, low resolution
Prompt
photo of of mexican woman bootlicker, ai company
Negative Prompt
cartoon, cgi, render, illustration, painting, drawing, bad quality, grainy, low resolution
Prompt
photo of a man bootlicker
Negative Prompt
cartoon, cgi, render, illustration, painting, drawing, bad quality, grainy, low resolution
Prompt
photo of a woman bootlicker
Negative Prompt
cartoon, cgi, render, illustration, painting, drawing, bad quality, grainy, low resolution
Prompt
photo of japanese man bootlicker
Negative Prompt
cartoon, cgi, render, illustration, painting, drawing, bad quality, grainy, low resolution

Model description

Create corporate headshots and portraits. Great for outpainiting a face for LinkedIn profile photos.

A weight of 0.5 works well in most models. Adjust as needed. Trigger word is "bootlicker".

Trigger words

You should use bootlicker to trigger the image generation.

Download model

Weights for this model are available in Safetensors format.

Download them in the Files & versions tab.

Use it with the 🧨 diffusers library

from diffusers import AutoPipelineForText2Image
import torch

pipeline = AutoPipelineForText2Image.from_pretrained('runwayml/stable-diffusion-v1-5', torch_dtype=torch.float16).to('cuda')
pipeline.load_lora_weights('ostris/bootlicker-corporate-photos-and-portraits', weight_name='bootlicker.safetensors')
image = pipeline('photo of  japanese  man bootlicker  ').images[0]

For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers

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