Edit model card

sd35-spirited-away-lokr

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 cat

Validation settings

  • CFG: 5.0
  • 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:

Prompt
unconditional (blank prompt)
Negative Prompt
blurry, cropped, ugly
Prompt
A scene from the animated Studio Ghibli movie Spirited Away, where a man with kind eyes and a worn hat sits by a window, lost in thought, as light filters gently through sheer curtains.
Negative Prompt
blurry, cropped, ugly
Prompt
A scene from the animated Studio Ghibli movie Spirited Away, where a woman with long, windswept hair reads a book at an outdoor cafe, surrounded by blooming flowers and soft afternoon light.
Negative Prompt
blurry, cropped, ugly
Prompt
A scene from the animated Studio Ghibli movie Spirited Away, where a fluffy white cat curls up on a windowsill, basking in the warm sunlight, while soft curtains flutter in the breeze.
Negative Prompt
blurry, cropped, ugly
Prompt
A scene from the animated Studio Ghibli movie Spirited Away, where a glowing, antlered spirit wanders through a quiet forest, leaving a trail of shimmering footprints among the ferns.
Negative Prompt
blurry, cropped, ugly
Prompt
A photo-realistic image of a cat
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: 6
  • Training steps: 1200
  • Learning rate: 1e-07
  • Max grad norm: 0.01
  • Effective batch size: 4
    • Micro-batch size: 4
    • Gradient accumulation steps: 1
    • Number of GPUs: 1
  • Prediction type: flow-matching
  • Rescaled betas zero SNR: False
  • Optimizer: adamw_bf16
  • Precision: Pure BF16
  • Quantised: Yes: int8-quanto
  • Xformers: Not used
  • LyCORIS Config:
{
    "bypass_mode": true,
    "algo": "lokr",
    "multiplier": 1.0,
    "linear_dim": 1000000,
    "linear_alpha": 1,
    "factor": 1,
    "full_matrix": true,
    "apply_preset": {
        "target_module": [
            "JointTransformerBlock"
        ],
        "name_algo_map": {
            "transformer_blocks.0.norm1*": {
                "algo": "lokr",
                "factor": 1,
                "linear_dim": 1000000,
                "linear_alpha": 1,
                "full_matrix": true
            },
            "transformer_blocks.0.norm1_context*": {
                "algo": "lokr",
                "factor": 1,
                "linear_dim": 1000000,
                "linear_alpha": 1,
                "full_matrix": true
            },
            "transformer_blocks.0.ff*": {
                "algo": "lokr",
                "factor": 1,
                "linear_dim": 1000000,
                "linear_alpha": 1,
                "full_matrix": true
            },
            "transformer_blocks.0.*": {
                "algo": "lokr",
                "factor": 2,
                "linear_dim": 1000000,
                "linear_alpha": 1,
                "full_matrix": true
            },
            "transformer_blocks.1.norm1*": {
                "algo": "lokr",
                "factor": 3,
                "linear_dim": 1000000,
                "linear_alpha": 1,
                "full_matrix": true
            },
            "transformer_blocks.1.norm1_context*": {
                "algo": "lokr",
                "factor": 3,
                "linear_dim": 1000000,
                "linear_alpha": 1,
                "full_matrix": true
            },
            "transformer_blocks.1.ff*": {
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                "factor": 3,
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            },
            "transformer_blocks.1.*": {
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                "factor": 6,
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                "linear_alpha": 1,
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            },
            "transformer_blocks.2.norm1*": {
                "algo": "lokr",
                "factor": 4,
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                "linear_alpha": 1,
                "full_matrix": true
            },
            "transformer_blocks.2.norm1_context*": {
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            },
            "transformer_blocks.2.ff*": {
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            },
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            },
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                "factor": 4,
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                "linear_alpha": 1,
                "full_matrix": true
            },
            "transformer_blocks.27.ff*": {
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                "linear_alpha": 1,
                "full_matrix": true
            },
            "transformer_blocks.27.*": {
                "algo": "lokr",
                "factor": 8,
                "linear_dim": 1000000,
                "linear_alpha": 1,
                "full_matrix": true
            },
            "transformer_blocks.28.norm1*": {
                "algo": "lokr",
                "factor": 4,
                "linear_dim": 1000000,
                "linear_alpha": 1,
                "full_matrix": true
            },
            "transformer_blocks.28.norm1_context*": {
                "algo": "lokr",
                "factor": 4,
                "linear_dim": 1000000,
                "linear_alpha": 1,
                "full_matrix": true
            },
            "transformer_blocks.28.ff*": {
                "algo": "lokr",
                "factor": 4,
                "linear_dim": 1000000,
                "linear_alpha": 1,
                "full_matrix": true
            },
            "transformer_blocks.28.*": {
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            },
            "transformer_blocks.29.norm1*": {
                "algo": "lokr",
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                "linear_alpha": 1,
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            },
            "transformer_blocks.29.norm1_context*": {
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                "full_matrix": true
            },
            "transformer_blocks.29.ff*": {
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            },
            "transformer_blocks.29.*": {
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            },
            "transformer_blocks.30.norm1*": {
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            },
            "transformer_blocks.30.norm1_context*": {
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            },
            "transformer_blocks.30.ff*": {
                "algo": "lokr",
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                "linear_alpha": 1,
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            },
            "transformer_blocks.30.*": {
                "algo": "lokr",
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                "linear_dim": 1000000,
                "linear_alpha": 1,
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            },
            "transformer_blocks.31.norm1*": {
                "algo": "lokr",
                "factor": 1,
                "linear_dim": 1000000,
                "linear_alpha": 1,
                "full_matrix": true
            },
            "transformer_blocks.31.norm1_context*": {
                "algo": "lokr",
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                "linear_dim": 1000000,
                "linear_alpha": 1,
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            },
            "transformer_blocks.31.ff*": {
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                "linear_alpha": 1,
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            },
            "transformer_blocks.31.*": {
                "algo": "lokr",
                "factor": 2,
                "linear_dim": 1000000,
                "linear_alpha": 1,
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            },
            "transformer_blocks.32.*": {
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            "transformer_blocks.33.ff*": {
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            "transformer_blocks.33.*": {
                "algo": "lokr",
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            },
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                "algo": "lokr",
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            "transformer_blocks.34.*": {
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                "full_matrix": true
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            "transformer_blocks.35.*": {
                "algo": "lokr",
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                "linear_alpha": 1,
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                "algo": "lokr",
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        },
        "use_fnmatch": true
    }
}

Datasets

screencaps-1024

  • Repeats: 0
  • Total number of images: 379
  • Total number of aspect buckets: 1
  • Resolution: 1.048576 megapixels
  • Cropped: False
  • Crop style: None
  • Crop aspect: None
  • Used for regularisation data: No

screencaps-1024-crop

  • Repeats: 0
  • Total number of images: 379
  • 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 cat"
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=5.0,
).images[0]
image.save("output.png", format="PNG")
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