jss_style, A young boy holds a small black dog in his arms. He wears a red bow tie and stands in front of a textured backdrop. His red socks and shoes are notable.

Validation settings

CFG: 4.2
CFG Rescale: 0.0
Steps: 30
Sampler: None
Seed: 42
Resolution: 1024x1024

Note: The validation settings are not necessarily the same as the training settings.

You can find some example images in the following gallery:

The text encoder was not trained. You may reuse the base model text encoder for inference.

Training settings

Training epochs: 9
Training steps: 6000
Learning rate: 8e-05
Effective batch size: 8
- Micro-batch size: 8
- Gradient accumulation steps: 1
- Number of GPUs: 1
Prediction type: epsilon
Rescaled betas zero SNR: False
Optimizer: adamw_bf16
Precision: Pure BF16
Quantised: Yes: int8-quanto
Xformers: Not used
LoRA Rank: 64
LoRA Alpha: None
LoRA Dropout: 0.1
LoRA initialisation style: default

Datasets

jss-sdxl-512

Repeats: 10
Total number of images: 84
Total number of aspect buckets: 7
Resolution: 0.262144 megapixels
Cropped: False
Crop style: None
Crop aspect: None

jss-sdxl-1024

Repeats: 10
Total number of images: 84
Total number of aspect buckets: 14
Resolution: 1.048576 megapixels
Cropped: False
Crop style: None
Crop aspect: None

jss-sdxl-512-crop

Repeats: 10
Total number of images: 84
Total number of aspect buckets: 1
Resolution: 0.262144 megapixels
Cropped: True
Crop style: random
Crop aspect: square

jss-sdxl-1024-crop

Repeats: 10
Total number of images: 84
Total number of aspect buckets: 1
Resolution: 1.048576 megapixels
Cropped: True
Crop style: random
Crop aspect: square

Inference

python

import torch
from diffusers import DiffusionPipeline

model_id = 'stabilityai/stable-diffusion-xl-base-1.0'
adapter_id = 'davidrd123/john-singer-sargent-sdxl-lora-03'
pipeline = DiffusionPipeline.from_pretrained(model_id)
pipeline.load_lora_weights(adapter_id)

prompt = "jss_style, A young boy holds a small black dog in his arms. He wears a red bow tie and stands in front of a textured backdrop. His red socks and shoes are notable."
negative_prompt = 'blurry, cropped, ugly'
pipeline.to('cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu')
image = pipeline(
    prompt=prompt,
    negative_prompt=negative_prompt,
    num_inference_steps=30,
    generator=torch.Generator(device='cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu').manual_seed(1641421826),
    width=1024,
    height=1024,
    guidance_scale=4.2,
    guidance_rescale=0.0,
).images[0]
image.save("output.png", format="PNG")