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simpletuner-lora

This is a LyCORIS adapter derived from sd3/unknown-model.

The main validation prompt used during training was:

Create an image of a fabric design featuring a classic camouflage pattern in various shades of green, brown, and black, suitable for military clothing and outdoor gear.

Validation settings

  • CFG: 3.0
  • CFG Rescale: 0.0
  • Steps: 20
  • Sampler: None
  • Seed: 42
  • Resolutions: 1024x1024,1280x768

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
unconditional (blank prompt)
Negative Prompt
blurry, cropped, ugly
Prompt
Create an image of a fabric design featuring a classic camouflage pattern in various shades of green, brown, and black, suitable for military clothing and outdoor gear.
Negative Prompt
blurry, cropped, ugly
Prompt
Create an image of a fabric design featuring a classic camouflage pattern in various shades of green, brown, and black, suitable for military clothing and outdoor gear.
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: 3500
  • Learning rate: 0.0001
  • Max grad norm: 0.01
  • Effective batch size: 1
    • Micro-batch size: 1
    • Gradient accumulation steps: 1
    • Number of GPUs: 1
  • Prediction type: flow-matching
  • Rescaled betas zero SNR: False
  • Optimizer: adamw_bf16
  • Precision: Pure BF16
  • Quantised: No
  • 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

GPTwebd3

  • Repeats: 0
  • Total number of images: 409
  • Total number of aspect buckets: 1
  • Resolution: 1.0 megapixels
  • Cropped: True
  • Crop style: center
  • Crop aspect: square
  • Used for regularisation data: No

Inference

import torch
from diffusers import DiffusionPipeline
from lycoris import create_lycoris_from_weights

model_id = '/root/autodl-tmp/stable-diffusion-3-medium-diffusers'
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 = "Create an image of a fabric design featuring a classic camouflage pattern in various shades of green, brown, and black, suitable for military clothing and outdoor gear."
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=3.0,
).images[0]
image.save("output.png", format="PNG")
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