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Flux.1-dev-LoKr-test1.2-0dropout

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 tommy chong

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
a photo of cheech marin
Negative Prompt
blurry, cropped, ugly
Prompt
a photo of cheech marin
Negative Prompt
blurry, cropped, ugly
Prompt
a photo of tommy chong
Negative Prompt
blurry, cropped, ugly
Prompt
a photo of tommy chong
Negative Prompt
blurry, cropped, ugly
Prompt
a photo with tommy chong sitting to the left of cheech marin
Negative Prompt
blurry, cropped, ugly
Prompt
a photo with tommy chong sitting to the left of cheech marin
Negative Prompt
blurry, cropped, ugly
Prompt
a photo with cheech marin sitting to the right of tommy chong
Negative Prompt
blurry, cropped, ugly
Prompt
a photo with cheech marin sitting to the right of tommy chong
Negative Prompt
blurry, cropped, ugly
Prompt
cheech and chong together in a photograph
Negative Prompt
blurry, cropped, ugly
Prompt
cheech and chong together in a photograph
Negative Prompt
blurry, cropped, ugly
Prompt
young cheech and chong in a black and white photograph
Negative Prompt
blurry, cropped, ugly
Prompt
young cheech and chong in a black and white photograph
Negative Prompt
blurry, cropped, ugly
Prompt
elderly cheech and chong in an interview on the BBC
Negative Prompt
blurry, cropped, ugly
Prompt
elderly cheech and chong in an interview on the BBC
Negative Prompt
blurry, cropped, ugly
Prompt
old tommy chong on a sitcom in the 1990s
Negative Prompt
blurry, cropped, ugly
Prompt
old tommy chong on a sitcom in the 1990s
Negative Prompt
blurry, cropped, ugly
Prompt
anime cheech marin
Negative Prompt
blurry, cropped, ugly
Prompt
anime cheech marin
Negative Prompt
blurry, cropped, ugly
Prompt
anime tommy chong
Negative Prompt
blurry, cropped, ugly
Prompt
anime tommy chong
Negative Prompt
blurry, cropped, ugly
Prompt
A photo-realistic image of a tommy chong
Negative Prompt
blurry, cropped, ugly
Prompt
A photo-realistic image of a tommy chong
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: 3100
  • Learning rate: 0.001
  • 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: optimi-stableadamwweight_decay=1e-3
  • 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

cheechandchong-512

  • Repeats: 100
  • Total number of images: ~24
  • Total number of aspect buckets: 5
  • Resolution: 0.262144 megapixels
  • Cropped: False
  • Crop style: None
  • Crop aspect: None

cheechandchong-1024

  • Repeats: 100
  • Total number of images: ~30
  • Total number of aspect buckets: 8
  • Resolution: 1.048576 megapixels
  • Cropped: False
  • Crop style: None
  • Crop aspect: None

cheechandchong-512-crop

  • Repeats: 100
  • Total number of images: ~18
  • Total number of aspect buckets: 1
  • Resolution: 0.262144 megapixels
  • Cropped: True
  • Crop style: random
  • Crop aspect: square

cheechandchong-1024-crop

  • Repeats: 100
  • Total number of images: ~18
  • Total number of aspect buckets: 1
  • Resolution: 1.048576 megapixels
  • Cropped: True
  • Crop style: random
  • Crop aspect: square

regularisation-512

  • Repeats: 0
  • Total number of images: ~5886
  • Total number of aspect buckets: 2
  • Resolution: 0.262144 megapixels
  • Cropped: False
  • Crop style: None
  • Crop aspect: None

regularisation-1024

  • Repeats: 0
  • Total number of images: ~5892
  • Total number of aspect buckets: 2
  • Resolution: 1.048576 megapixels
  • Cropped: False
  • Crop style: None
  • Crop aspect: None

regularisation-512-crop

  • Repeats: 0
  • Total number of images: ~5874
  • Total number of aspect buckets: 1
  • Resolution: 0.262144 megapixels
  • Cropped: True
  • Crop style: random
  • Crop aspect: square

regularisation-1024-crop

  • Repeats: 0
  • Total number of images: ~5874
  • 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 tommy chong"

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")
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