metadata
license: creativeml-openrail-m
base_model: stabilityai/stable-diffusion-xl-base-1.0
tags:
- sdxl
- sdxl-diffusers
- text-to-image
- diffusers
- simpletuner
- not-for-all-audiences
- lora
- template:sd-lora
- lycoris
inference: true
widget:
- text: unconditional (blank prompt)
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/image_0_0.png
- text: >-
ggn_style, Five women are in a field. Two women on the right stand, one
with arms outstretched, the other in a pink headscarf. A nude woman in the
center stretches upward. Two nude women sit on the left, facing forward.
Trees and hills are in the backgrou
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/image_1_0.png
paul-gaugin-sdxl-lora-2
This is a LyCORIS adapter derived from stabilityai/stable-diffusion-xl-base-1.0.
The main validation prompt used during training was:
ggn_style, Five women are in a field. Two women on the right stand, one with arms outstretched, the other in a pink headscarf. A nude woman in the center stretches upward. Two nude women sit on the left, facing forward. Trees and hills are in the backgrou
Validation settings
- CFG:
4.2
- CFG Rescale:
0.0
- Steps:
20
- 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: 7000
- Learning rate: 0.0001
- Effective batch size: 4
- Micro-batch size: 4
- Gradient accumulation steps: 1
- Number of GPUs: 1
- Prediction type: epsilon
- Rescaled betas zero SNR: False
- Optimizer: optimi-stableadamw
- Precision: Pure BF16
- Quantised: Yes: int8-quanto
- Xformers: Not used
- LyCORIS Config:
{
"algo": "lokr",
"multiplier": 1.0,
"linear_dim": 10000,
"linear_alpha": 1,
"factor": 16,
"apply_preset": {
"target_module": [
"Attention",
"FeedForward"
],
"module_algo_map": {
"Attention": {
"factor": 16
},
"FeedForward": {
"factor": 8
}
}
}
}
Datasets
paul-gaugin-sdxl-512
- Repeats: 6
- Total number of images: 87
- Total number of aspect buckets: 1
- Resolution: 0.262144 megapixels
- Cropped: False
- Crop style: None
- Crop aspect: None
paul-gaugin-sdxl-1024
- Repeats: 6
- Total number of images: 87
- Total number of aspect buckets: 17
- Resolution: 1.048576 megapixels
- Cropped: False
- Crop style: None
- Crop aspect: None
paul-gaugin-sdxl-512-crop
- Repeats: 6
- Total number of images: 87
- Total number of aspect buckets: 1
- Resolution: 0.262144 megapixels
- Cropped: True
- Crop style: random
- Crop aspect: square
paul-gaugin-sdxl-1024-crop
- Repeats: 6
- Total number of images: 87
- Total number of aspect buckets: 1
- Resolution: 1.048576 megapixels
- Cropped: True
- Crop style: random
- Crop aspect: square
Inference
import torch
from diffusers import DiffusionPipeline
from lycoris import create_lycoris_from_weights
model_id = 'stabilityai/stable-diffusion-xl-base-1.0'
adapter_id = 'pytorch_lora_weights.safetensors' # you will have to download this manually
lora_scale = 1.0
wrapper, _ = create_lycoris_from_weights(lora_scale, adapter_id, pipeline.transformer)
wrapper.merge_to()
prompt = "ggn_style, Five women are in a field. Two women on the right stand, one with arms outstretched, the other in a pink headscarf. A nude woman in the center stretches upward. Two nude women sit on the left, facing forward. Trees and hills are in the backgrou"
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=20,
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")