simpletuner-lora

This is a standard PEFT LoRA derived from black-forest-labs/FLUX.1-dev.

The main validation prompt used during training was:

A picture of Philippe

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 breathtaking anime-style portrait of Philippe, capturing his essence with vibrant colors and expressive features
Negative Prompt
blurry, cropped, ugly
Prompt
a high-quality, detailed photograph of Philippe as a sous-chef, immersed in the art of culinary creation
Negative Prompt
blurry, cropped, ugly
Prompt
a lifelike and intimate portrait of Philippe, showcasing his unique personality and charm
Negative Prompt
blurry, cropped, ugly
Prompt
a cinematic, visually stunning photo of Philippe, emphasizing his dramatic and captivating presence
Negative Prompt
blurry, cropped, ugly
Prompt
an elegant and timeless portrait of Philippe, exuding grace and sophistication
Negative Prompt
blurry, cropped, ugly
Prompt
a dynamic and adventurous photo of Philippe, captured in an exciting, action-filled moment
Negative Prompt
blurry, cropped, ugly
Prompt
a mysterious and enigmatic portrait of Philippe, shrouded in shadows and intrigue
Negative Prompt
blurry, cropped, ugly
Prompt
a vintage-style portrait of Philippe, evoking the charm and nostalgia of a bygone era
Negative Prompt
blurry, cropped, ugly
Prompt
an artistic and abstract representation of Philippe, blending creativity with visual storytelling
Negative Prompt
blurry, cropped, ugly
Prompt
a futuristic and cutting-edge portrayal of Philippe, set against a backdrop of advanced technology
Negative Prompt
blurry, cropped, ugly
Prompt
A picture of Philippe
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: 636
  • Training steps: 7000
  • Learning rate: 0.0001
  • Effective batch size: 1
    • Micro-batch size: 1
    • Gradient accumulation steps: 1
    • Number of GPUs: 1
  • Prediction type: flow-matching
  • Rescaled betas zero SNR: False
  • Optimizer: adamw_bf16
  • Precision: Pure BF16
  • Quantised: No
  • Xformers: Not used
  • LoRA Rank: 16
  • LoRA Alpha: None
  • LoRA Dropout: 0.1
  • LoRA initialisation style: default

Datasets

dreambooth-subject

  • Repeats: 0
  • Total number of images: 11
  • Total number of aspect buckets: 1
  • Resolution: 1.048576 megapixels
  • Cropped: False
  • Crop style: None
  • Crop aspect: None

Inference

import torch
from diffusers import DiffusionPipeline

model_id = 'black-forest-labs/FLUX.1-dev'
adapter_id = 'PhilSad/simpletuner-lora'
pipeline = DiffusionPipeline.from_pretrained(model_id)
pipeline.load_lora_weights(adapter_id)

prompt = "A picture of Philippe"

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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