metadata
license: other
license_name: bespoke-lora-trained-license
license_link: >-
https://multimodal.art/civitai-licenses?allowNoCredit=False&allowCommercialUse=Image&allowDerivatives=True&allowDifferentLicense=True
tags:
- text-to-image
- stable-diffusion
- lora
- diffusers
- template:sd-lora
- migrated
- people
- tool
- slider
- number of people
base_model: runwayml/stable-diffusion-v1-5
instance_prompt: null
widget:
- text: 'hipster men at a bar posing for a picture '
parameters:
negative_prompt: >-
shirtless, nude, cartoon, cgi, render, illustration, painting, drawing,
bad quality, grainy, low resolution
output:
url: 1670646.jpeg
- text: 'hipster men at a bar posing for a picture '
parameters:
negative_prompt: >-
shirtless, nude, cartoon, cgi, render, illustration, painting, drawing,
bad quality, grainy, low resolution
output:
url: 1670739.jpeg
- text: 'hipster men at a bar posing for a picture '
parameters:
negative_prompt: >-
shirtless, nude, cartoon, cgi, render, illustration, painting, drawing,
bad quality, grainy, low resolution
output:
url: 1670714.jpeg
- text: 'hipster men at a bar posing for a picture '
parameters:
negative_prompt: >-
shirtless, nude, cartoon, cgi, render, illustration, painting, drawing,
bad quality, grainy, low resolution
output:
url: 1670719.jpeg
- text: 'hipster men at a bar posing for a picture '
parameters:
negative_prompt: >-
shirtless, nude, cartoon, cgi, render, illustration, painting, drawing,
bad quality, grainy, low resolution
output:
url: 1670723.jpeg
- text: ' '
output:
url: 1671159.jpeg
People Count Slider - LoRA
Model description
Weights can swing very far on this one -8.0 to +8.0. It can do extremely large crowds the higher you go and I wanted to be able to keep granular control.
Positive = More people
Negative = Less people
Simple LoRA to help with adjusting the number of people in a picture. You can swing it both ways pretty far out from -8 to +8 without much distortion.
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/people-count-slider-lora', weight_name='people_count_slider_v1.safetensors')
image = pipeline('Your custom prompt').images[0]
For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers