metadata
license: creativeml-openrail-m
base_model: stabilityai/stable-diffusion-xl-base-1.0
tags:
- sdxl
- sdxl-diffusers
- text-to-image
- diffusers
- simpletuner
- safe-for-work
- 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: bdn_style, painting of a hipster making a chair
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/image_1_0.png
- text: bdn_style, painting of a hamster
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/image_2_0.png
- text: >-
in the style of bdn_style, A bustling coastal market scene under a
dramatic, stormy sky. Vendors with colorful umbrellas sell their wares as
dark clouds gather overhead. Fishing boats bob in the choppy harbor
waters. A lighthouse stands sentinel in the distance, its beam cutting
through the approaching tempest.
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/image_3_0.png
- text: >-
bdn_style, A group of elegantly dressed people enjoying a picnic on the
beach at sunset. The sky is ablaze with vibrant oranges and purples,
reflecting off the calm sea. Parasols and blankets dot the sand, while a
steam train puffs along a distant coastal track, leaving a trail of smoke
that merges with the clouds.
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/image_4_0.png
- text: bdn_style, an airliner flying over a body of water at sunset
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/image_5_0.png
- text: >-
bdn_style, A harbor at sunset. Multiple ships with masts and sails are
anchored. Small rowboat with two people in the water. Pier extends from
left. Land with trees and buildings in the background. Text at bottom
left.
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/image_6_0.png
eugene-boudin-sdxl-01
This is a LyCORIS adapter derived from stabilityai/stable-diffusion-xl-base-1.0.
The main validation prompt used during training was:
bdn_style, A harbor at sunset. Multiple ships with masts and sails are anchored. Small rowboat with two people in the water. Pier extends from left. Land with trees and buildings in the background. Text at bottom left.
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: 15
- Training steps: 10000
- 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-lionweight_decay=1e-3
- 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
eugene-boudin-sdxl-512
- Repeats: 10
- Total number of images: 53
- Total number of aspect buckets: 4
- Resolution: 0.262144 megapixels
- Cropped: False
- Crop style: None
- Crop aspect: None
eugene-boudin-sdxl-1024
- Repeats: 10
- Total number of images: 53
- Total number of aspect buckets: 2
- Resolution: 1.048576 megapixels
- Cropped: False
- Crop style: None
- Crop aspect: None
eugene-boudin-sdxl-512-crop
- Repeats: 10
- Total number of images: 53
- Total number of aspect buckets: 1
- Resolution: 0.262144 megapixels
- Cropped: True
- Crop style: random
- Crop aspect: square
eugene-boudin-sdxl-1024-crop
- Repeats: 10
- Total number of images: 53
- 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 = "bdn_style, A harbor at sunset. Multiple ships with masts and sails are anchored. Small rowboat with two people in the water. Pier extends from left. Land with trees and buildings in the background. Text at bottom left."
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")