README.md

metadata

license: other
base_model: black-forest-labs/FLUX.1-dev
tags:
  - flux
  - flux-diffusers
  - text-to-image
  - diffusers
  - simpletuner
  - lora
  - template:sd-lora
inference: true
widget:
  - text: unconditional (blank prompt)
    parameters:
      negative_prompt: blurry, cropped, ugly
    output:
      url: ./assets/image_0_0.png
  - text: a juggalo performing miracles at a festival
    parameters:
      negative_prompt: blurry, cropped, ugly
    output:
      url: ./assets/image_1_0.png
  - text: a juggalo man and woman in a close-up portrait smiling and happy
    parameters:
      negative_prompt: blurry, cropped, ugly
    output:
      url: ./assets/image_2_0.png
  - text: a juggalo family portrait
    parameters:
      negative_prompt: blurry, cropped, ugly
    output:
      url: ./assets/image_3_0.png
  - text: a juggalo teacher giving a lesson to a classroom of juggalo students
    parameters:
      negative_prompt: blurry, cropped, ugly
    output:
      url: ./assets/image_4_0.png
  - text: a toddler juggalo criminal mugshot 1998 olan mills studio photography
    parameters:
      negative_prompt: blurry, cropped, ugly
    output:
      url: ./assets/image_5_0.png
  - text: a baby juggalo welder working on the titanic, 1912, sepia
    parameters:
      negative_prompt: blurry, cropped, ugly
    output:
      url: ./assets/image_6_0.png
  - text: >-
      a baby juggalo news anchor on the insane clown news network wearing
      glasses
    parameters:
      negative_prompt: blurry, cropped, ugly
    output:
      url: ./assets/image_7_0.png
  - text: a juggalo holding a sign that says keepin it real
    parameters:
      negative_prompt: blurry, cropped, ugly
    output:
      url: ./assets/image_8_0.png

flux-juggalos-lokr

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

The main validation prompt used during training was:

a juggalo holding a sign that says keepin it real

Validation settings

• CFG: 3.4
• CFG Rescale: 0.0
• Steps: 25
• 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 juggalo performing miracles at a festival

Negative Prompt

blurry, cropped, ugly

Prompt

a juggalo man and woman in a close-up portrait smiling and happy

Negative Prompt

blurry, cropped, ugly

Prompt

a juggalo family portrait

Negative Prompt

blurry, cropped, ugly

Prompt

a juggalo teacher giving a lesson to a classroom of juggalo students

Negative Prompt

blurry, cropped, ugly

Prompt

a toddler juggalo criminal mugshot 1998 olan mills studio photography

Negative Prompt

blurry, cropped, ugly

Prompt

a baby juggalo welder working on the titanic, 1912, sepia

Negative Prompt

blurry, cropped, ugly

Prompt

a baby juggalo news anchor on the insane clown news network wearing glasses

Negative Prompt

blurry, cropped, ugly

Prompt

a juggalo holding a sign that says keepin it real

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: 8
• Training steps: 2500
• Learning rate: 5e-06
• Effective batch size: 12
  • Micro-batch size: 6
  • Gradient accumulation steps: 1
  • Number of GPUs: 2
• Prediction type: flow-matching
• Rescaled betas zero SNR: False
• Optimizer: optimi-lion
• Precision: bf16
• Quantised: No
• 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

juggalos-aspect-bucket

• Repeats: 10
• Total number of images: ~26
• Total number of aspect buckets: 7
• Resolution: 0.262144 megapixels
• Cropped: False
• Crop style: None
• Crop aspect: None

juggalos-crop

• Repeats: 10
• Total number of images: ~22
• Total number of aspect buckets: 1
• Resolution: 0.262144 megapixels
• Cropped: True
• Crop style: random
• Crop aspect: square

juggalos-aspect-bucket-1mp

• Repeats: 10
• Total number of images: ~26
• Total number of aspect buckets: 8
• Resolution: 1.048576 megapixels
• Cropped: False
• Crop style: None
• Crop aspect: None

juggalos-crop-1mp

• Repeats: 10
• Total number of images: ~20
• 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 juggalo holding a sign that says keepin it real"

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=25,
    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=3.4,
).images[0]
image.save("output.png", format="PNG")