Training epochs: 0
Training steps: 100
Learning rate: 0.0008
Effective batch size: 16
- Micro-batch size: 4
- Gradient accumulation steps: 4
- Number of GPUs: 1
Prediction type: flow-matching
Rescaled betas zero SNR: False
Optimizer: adamw_bf16
Precision: bf16
Quantised: No
Xformers: Not used
LoRA Rank: 16
LoRA Alpha: None
LoRA Dropout: 0.1
LoRA initialisation style: default

Datasets

default_dataset_arb

Repeats: 100
Total number of images: 4
Total number of aspect buckets: 3
Resolution: 1.5 megapixels
Cropped: False
Crop style: None
Crop aspect: None

default_dataset

Repeats: 100
Total number of images: 3
Total number of aspect buckets: 1
Resolution: 1.048576 megapixels
Cropped: True
Crop style: random
Crop aspect: square

default_dataset_512

Repeats: 100
Total number of images: 4
Total number of aspect buckets: 1
Resolution: 0.262144 megapixels
Cropped: True
Crop style: random
Crop aspect: square

default_dataset_576

Repeats: 100
Total number of images: 4
Total number of aspect buckets: 1
Resolution: 0.331776 megapixels
Cropped: True
Crop style: random
Crop aspect: square

default_dataset_640

Repeats: 100
Total number of images: 4
Total number of aspect buckets: 1
Resolution: 0.4096 megapixels
Cropped: True
Crop style: random
Crop aspect: square

default_dataset_704

Repeats: 100
Total number of images: 4
Total number of aspect buckets: 1
Resolution: 0.495616 megapixels
Cropped: True
Crop style: random
Crop aspect: square

default_dataset_768

Repeats: 100
Total number of images: 3
Total number of aspect buckets: 1
Resolution: 0.589824 megapixels
Cropped: True
Crop style: random
Crop aspect: square

default_dataset_832

Repeats: 100
Total number of images: 3
Total number of aspect buckets: 1
Resolution: 0.692224 megapixels
Cropped: True
Crop style: random
Crop aspect: square

default_dataset_896

Repeats: 100
Total number of images: 3
Total number of aspect buckets: 1
Resolution: 0.802816 megapixels
Cropped: True
Crop style: random
Crop aspect: square

default_dataset_960

Repeats: 100
Total number of images: 3
Total number of aspect buckets: 1
Resolution: 0.9216 megapixels
Cropped: True
Crop style: random
Crop aspect: square

Inference

python

import torch
from diffusers import DiffusionPipeline

model_id = 'black-forest-labs/FLUX.1-dev'
adapter_id = 'jimmycarter/flux-training-seuss-lora'
pipeline = DiffusionPipeline.from_pretrained(model_id)
pipeline.load_lora_weights(adapter_id)

prompt = "A photograph of Dr. Seuss riding in a horse-drawn carriage"

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=15,
    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=3.5,
).images[0]
image.save("output.png", format="PNG")