metadata
license: other
base_model: stabilityai/stable-diffusion-3.5-large
tags:
- sd3
- sd3-diffusers
- text-to-image
- diffusers
- simpletuner
- safe-for-work
- lora
- template:sd-lora
- standard
inference: true
widget:
- text: unconditional (blank prompt)
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/image_0_0.png
- text: >-
A pixel art sprite of majestic water and dark-element cat. It evolved for
full, featuring slender graceful body. The cat has sleek, shadowy black
fur with glowing blue wave-like patterns flowing across its body. Its
piercing blue eyes glow with an ethereal light, and its tail curls in a
spiral, resembling a dark water vortex. Small floating water droplets and
ghostly blue mist surround the cat, enhancing its mysterious aura. The
background is dark to contrast the bright neon blue elements, with
pixelated waves and shadowy mist effects. Created using high-detail pixel
art, vibrant color balance, and dynamic lighting effects.
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/image_1_0.png
0211
This is a standard PEFT LoRA derived from stabilityai/stable-diffusion-3.5-large.
The main validation prompt used during training was:
A pixel art sprite of majestic water and dark-element cat. It evolved for full, featuring slender graceful body. The cat has sleek, shadowy black fur with glowing blue wave-like patterns flowing across its body. Its piercing blue eyes glow with an ethereal light, and its tail curls in a spiral, resembling a dark water vortex. Small floating water droplets and ghostly blue mist surround the cat, enhancing its mysterious aura. The background is dark to contrast the bright neon blue elements, with pixelated waves and shadowy mist effects. Created using high-detail pixel art, vibrant color balance, and dynamic lighting effects.
Validation settings
- CFG:
5.0 - CFG Rescale:
0.0 - Steps:
20 - Sampler:
FlowMatchEulerDiscreteScheduler - Seed:
42 - Resolution:
1024x1024 - Skip-layer guidance:
Note: The validation settings are not necessarily the same as the training settings.
You can find some example images in the following gallery:
- Prompt
- unconditional (blank prompt)
- Negative Prompt
- blurry, cropped, ugly
- Prompt
- A pixel art sprite of majestic water and dark-element cat. It evolved for full, featuring slender graceful body. The cat has sleek, shadowy black fur with glowing blue wave-like patterns flowing across its body. Its piercing blue eyes glow with an ethereal light, and its tail curls in a spiral, resembling a dark water vortex. Small floating water droplets and ghostly blue mist surround the cat, enhancing its mysterious aura. The background is dark to contrast the bright neon blue elements, with pixelated waves and shadowy mist effects. Created using high-detail pixel art, vibrant color balance, and dynamic lighting effects.
- Negative Prompt
- blurry, cropped, ugly
The text encoder was not trained. You may reuse the base model text encoder for inference.
Training settings
Training epochs: 8
Training steps: 10000
Learning rate: 8e-05
- Learning rate schedule: polynomial
- Warmup steps: 100
Max grad norm: 2.0
Effective batch size: 1
- Micro-batch size: 1
- Gradient accumulation steps: 1
- Number of GPUs: 1
Gradient checkpointing: True
Prediction type: flow-matching (extra parameters=['shift=3'])
Optimizer: adamw_bf16
Trainable parameter precision: Pure BF16
Caption dropout probability: 5.0%
LoRA Rank: 64
LoRA Alpha: None
LoRA Dropout: 0.1
LoRA initialisation style: default
Datasets
dataset-1024
- Repeats: 10
- Total number of images: 53
- Total number of aspect buckets: 1
- Resolution: 1.048576 megapixels
- Cropped: False
- Crop style: None
- Crop aspect: None
- Used for regularisation data: No
dataset-crop-1024
- Repeats: 10
- Total number of images: 53
- Total number of aspect buckets: 1
- Resolution: 1.048576 megapixels
- Cropped: True
- Crop style: center
- Crop aspect: square
- Used for regularisation data: No
Inference
import torch
from diffusers import DiffusionPipeline
model_id = 'stabilityai/stable-diffusion-3.5-large'
adapter_id = 'badul13/0211'
pipeline = DiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.bfloat16) # loading directly in bf16
pipeline.load_lora_weights(adapter_id)
prompt = "A pixel art sprite of majestic water and dark-element cat. It evolved for full, featuring slender graceful body. The cat has sleek, shadowy black fur with glowing blue wave-like patterns flowing across its body. Its piercing blue eyes glow with an ethereal light, and its tail curls in a spiral, resembling a dark water vortex. Small floating water droplets and ghostly blue mist surround the cat, enhancing its mysterious aura. The background is dark to contrast the bright neon blue elements, with pixelated waves and shadowy mist effects. Created using high-detail pixel art, vibrant color balance, and dynamic lighting effects."
negative_prompt = 'blurry, cropped, ugly'
## Optional: quantise the model to save on vram.
## Note: The model was quantised during training, and so it is recommended to do the same during inference time.
from optimum.quanto import quantize, freeze, qint8
quantize(pipeline.transformer, weights=qint8)
freeze(pipeline.transformer)
pipeline.to('cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu') # the pipeline is already in its target precision level
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(42),
width=1024,
height=1024,
guidance_scale=5.0,
).images[0]
image.save("output.png", format="PNG")