moon_synthetic_hipster

This is a LyCORIS adapter derived from black-forest-labs/FLUX.1-dev.

No validation prompt was used during training.

None

Validation settings

CFG: 3.0
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 hamster in the style of m00nl4nd1ng

Negative Prompt
blurry, cropped, ugly

Prompt
an astronaut hamster in the style of m00nl4nd1ng

Negative Prompt
blurry, cropped, ugly

Prompt
woman holding a sign that says 'I LOVE PROMPTS!' in the style of m00nl4nd1ng

Negative Prompt
blurry, cropped, ugly

Prompt
a hipster man with a beard, building a chair in the style of m00nl4nd1ng

Negative Prompt
blurry, cropped, ugly

Prompt
Cat with lasers shooting out of its eyes in the style of m00nl4nd1ng

Negative Prompt
blurry, cropped, ugly

Prompt
sports event, athlete in motion, crowd blurred, flare from stadium lights in the style of m00nl4nd1ng

Negative Prompt
blurry, cropped, ugly

Prompt
a man holding a sign that says, 'this is a sign'

Negative Prompt
blurry, cropped, ugly

Prompt
a pig, in a post apocalyptic world, with a shotgun, in a leather jacket, in a desert, with a motorcycle

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: 9
Training steps: 3500
Learning rate: 0.0002
Max grad norm: 0.1
Effective batch size: 4
- Micro-batch size: 4
- Gradient accumulation steps: 1
- Number of GPUs: 1
Prediction type: flow-matching (flux parameters=['shift=3', 'flux_guidance_value=1.0'])
Rescaled betas zero SNR: False
Optimizer: adamw_bf16
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

moonsynth-512

Repeats: 15
Total number of images: 39
Total number of aspect buckets: 1
Resolution: 0.262144 megapixels
Cropped: False
Crop style: None
Crop aspect: None
Used for regularisation data: No

moonsynth-768

Repeats: 15
Total number of images: 39
Total number of aspect buckets: 1
Resolution: 0.589824 megapixels
Cropped: False
Crop style: None
Crop aspect: None
Used for regularisation data: No

moonsynth-1024

Repeats: 7
Total number of images: 21
Total number of aspect buckets: 1
Resolution: 1.048576 megapixels
Cropped: False
Crop style: None
Crop aspect: None
Used for regularisation data: No

Inference

import torch
from diffusers import DiffusionPipeline
from lycoris import create_lycoris_from_weights

model_id = 'black-forest-labs/FLUX.1-dev'
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 = "An astronaut is riding a horse through the jungles of Thailand."

pipeline.to('cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu')
image = pipeline(
    prompt=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")

mipat12
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moon_synthetic_hipster