simpletuner-lora

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

The main validation prompt used during training was:

A photo-realistic image of a cat

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 garfield waifu wearing an apron with a red sphere over her head that reads It is Time

Negative Prompt
blurry, cropped, ugly

Prompt
a void of fursuit furries hanging onto the edge of reality as they get sucked into a vortex

Negative Prompt
blurry, cropped, ugly

Prompt
furries collect at walmart to teach about gelatin fountains

Negative Prompt
blurry, cropped, ugly

Prompt
a sugar bear named brownie plays basketball with lumps of poop

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: 0
Training steps: 2000
Learning rate: 6e-05
Effective batch size: 6
- Micro-batch size: 2
- Gradient accumulation steps: 1
- Number of GPUs: 3
Prediction type: flow-matching
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": 12,
    "apply_preset": {
        "target_module": [
            "Attention",
            "FeedForward"
        ],
        "module_algo_map": {
            "Attention": {
                "factor": 12
            },
            "FeedForward": {
                "factor": 6
            }
        }
    }
}

Datasets

sfwbooru

Repeats: 0
Total number of images: ~639264
Total number of aspect buckets: 78
Resolution: 1.048576 megapixels
Cropped: False
Crop style: None
Crop aspect: None

normalnudes

Repeats: 50
Total number of images: ~1233
Total number of aspect buckets: 31
Resolution: 1.048576 megapixels
Cropped: False
Crop style: None
Crop aspect: None

guys

Repeats: 0
Total number of images: ~390
Total number of aspect buckets: 16
Resolution: 1.048576 megapixels
Cropped: False
Crop style: None
Crop aspect: None

signs

Repeats: 0
Total number of images: ~435
Total number of aspect buckets: 19
Resolution: 1.048576 megapixels
Cropped: False
Crop style: None
Crop aspect: None

nsfw-1024

Repeats: 0
Total number of images: ~10830
Total number of aspect buckets: 14
Resolution: 1.048576 megapixels
Cropped: False
Crop style: None
Crop aspect: None

anatomy

Repeats: 2
Total number of images: ~16440
Total number of aspect buckets: 24
Resolution: 1.048576 megapixels
Cropped: False
Crop style: None
Crop aspect: None

yoga

Repeats: 0
Total number of images: ~3642
Total number of aspect buckets: 20
Resolution: 1.048576 megapixels
Cropped: False
Crop style: None
Crop aspect: None

photo-aesthetics

Repeats: 0
Total number of images: ~33171
Total number of aspect buckets: 30
Resolution: 1.048576 megapixels
Cropped: False
Crop style: None
Crop aspect: None

text-1mp

Repeats: 125
Total number of images: ~13221
Total number of aspect buckets: 25
Resolution: 1.048576 megapixels
Cropped: False
Crop style: None
Crop aspect: None

normalnudes-crop

Repeats: 50
Total number of images: ~1146
Total number of aspect buckets: 1
Resolution: 1.048576 megapixels
Cropped: True
Crop style: random
Crop aspect: square

guys-crop

Repeats: 0
Total number of images: ~381
Total number of aspect buckets: 1
Resolution: 1.048576 megapixels
Cropped: True
Crop style: random
Crop aspect: square

signs-crop

Repeats: 0
Total number of images: ~417
Total number of aspect buckets: 1
Resolution: 1.048576 megapixels
Cropped: True
Crop style: random
Crop aspect: square

nsfw-1024-crop

Repeats: 0
Total number of images: ~10818
Total number of aspect buckets: 1
Resolution: 1.048576 megapixels
Cropped: True
Crop style: random
Crop aspect: square

anatomy-crop

Repeats: 2
Total number of images: ~16425
Total number of aspect buckets: 1
Resolution: 1.048576 megapixels
Cropped: True
Crop style: random
Crop aspect: square

yoga-crop

Repeats: 0
Total number of images: ~3618
Total number of aspect buckets: 1
Resolution: 1.048576 megapixels
Cropped: True
Crop style: random
Crop aspect: square

photo-aesthetics-crop

Repeats: 0
Total number of images: ~33141
Total number of aspect buckets: 1
Resolution: 1.048576 megapixels
Cropped: True
Crop style: random
Crop aspect: square

text-1mp-crop

Repeats: 125
Total number of images: ~13194
Total number of aspect buckets: 1
Resolution: 1.048576 megapixels
Cropped: True
Crop style: random
Crop aspect: square

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 = "A photo-realistic image of a cat"

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")

bghira
/

simpletuner-lora