metadata
license: other
base_model: stabilityai/stable-diffusion-3.5-large
tags:
- sd3
- sd3-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: unconditional (blank prompt)
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/image_1_1.png
- text: unconditional (blank prompt)
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/image_2_2.png
- text: >-
a photo-realistic image of a Napoleon Dynamite man wearing a bedazzled
gymnast's leotard, standing triumphantly on the winner's podium with a
large gold medal hanging from it's blue ribbon displayed proudly on his
chest. power pose, smile, high quality
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/image_3_0.png
- text: >-
a photo-realistic image of a Napoleon Dynamite man wearing a bedazzled
gymnast's leotard, standing triumphantly on the winner's podium with a
large gold medal hanging from it's blue ribbon displayed proudly on his
chest. power pose, smile, high quality
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/image_4_1.png
- text: >-
a photo-realistic image of a Napoleon Dynamite man wearing a bedazzled
gymnast's leotard, standing triumphantly on the winner's podium with a
large gold medal hanging from it's blue ribbon displayed proudly on his
chest. power pose, smile, high quality
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/image_5_2.png
napoleon-lokr-multi
This is a LyCORIS adapter derived from stabilityai/stable-diffusion-3.5-large.
The main validation prompt used during training was:
a photo-realistic image of a Napoleon Dynamite man wearing a bedazzled gymnast's leotard, standing triumphantly on the winner's podium with a large gold medal hanging from it's blue ribbon displayed proudly on his chest. power pose, smile, high quality
Validation settings
- CFG:
4.0
- CFG Rescale:
0.0
- Steps:
20
- Sampler:
None
- Seed:
1404
- Resolutions:
1024x1024, 896x1152, 1216x832
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: 6
- Training steps: 5000
- Learning rate: 0.00016
- Max grad norm: 0.01
- Effective batch size: 4
- Micro-batch size: 1
- Gradient accumulation steps: 1
- Number of GPUs: 4
- Prediction type: flow-matching
- Rescaled betas zero SNR: False
- Optimizer: adamw_bf16
- Precision: Pure BF16
- Quantised: No
- Xformers: Not used
- LyCORIS Config:
{
"bypass_mode": true,
"algo": "lokr",
"multiplier": 1.0,
"full_matrix": true,
"linear_dim": 10000,
"linear_alpha": 1,
"factor": 12,
"apply_preset": {
"target_module": [
"Attention"
],
"module_algo_map": {
"Attention": {
"factor": 6
}
}
}
}
Datasets
napoleon-512
- Repeats: 10
- Total number of images: ~84
- Total number of aspect buckets: 6
- Resolution: 0.262144 megapixels
- Cropped: False
- Crop style: None
- Crop aspect: None
- Used for regularisation data: No
napoleon-1024
- Repeats: 10
- Total number of images: ~60
- Total number of aspect buckets: 3
- Resolution: 1.048576 megapixels
- Cropped: False
- Crop style: None
- Crop aspect: None
- Used for regularisation data: No
napoleon-512-crop
- Repeats: 10
- Total number of images: ~72
- Total number of aspect buckets: 1
- Resolution: 0.262144 megapixels
- Cropped: True
- Crop style: random
- Crop aspect: square
- Used for regularisation data: No
napoleon-1024-crop
- Repeats: 10
- Total number of images: ~44
- Total number of aspect buckets: 1
- Resolution: 1.048576 megapixels
- Cropped: True
- Crop style: random
- Crop aspect: square
- Used for regularisation data: No
Inference
import torch
from diffusers import DiffusionPipeline
from lycoris import create_lycoris_from_weights
model_id = 'stabilityai/stable-diffusion-3.5-large'
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 = "a photo-realistic image of a Napoleon Dynamite man wearing a bedazzled gymnast's leotard, standing triumphantly on the winner's podium with a large gold medal hanging from it's blue ribbon displayed proudly on his chest. power pose, smile, high quality"
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=4.0,
).images[0]
image.save("output.png", format="PNG")