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flux-test-q1sV8

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

The main validation prompt used during training was:

a photo of a q1s woman in a hoodie and skirt on the beach

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 photo of a q1s woman in a suit standing on the streets of Tokyo
Negative Prompt
blurry, cropped, ugly
Prompt
anime of a q1s woman in school uniform standing on a bridge
Negative Prompt
blurry, cropped, ugly
Prompt
photo of a q1s woman in leather jacket on the beach
Negative Prompt
blurry, cropped, ugly
Prompt
A stunning portrait of a sophisticated q1s woman adorned with a luxurious wide-brimmed red hat that elegantly covers part of her face, illustration, vibrant, portrait photography
Negative Prompt
blurry, cropped, ugly
Prompt
A grainy, sepia-toned photograph taken with a Kodak Portra 400 film camera in the late 1990s. A young q1s woman with captivating gaze poses confidently. She wears a vintage, black MinMin T-shirt, slightly oversized and slightly worn, with the band's iconic logo prominently displayed. The background is blurred, suggesting a dimly lit, underground music venue or a friend's basement.
Negative Prompt
blurry, cropped, ugly
Prompt
A captivating minimalist masterpiece showcases a q1s woman exuding elegance and tranquility. The beautiful subject is dressed in a linen dress, featuring pastel beige and light grey hues. The background consists of a harmonious composition of rectangles and squares, subtly outlined in black pencil. This vibrant and conceptual artwork elicits a cinematic and fashionable illustration.
Negative Prompt
blurry, cropped, ugly
Prompt
a digital painting of a q1s woman in a green hoodie and purple skirt standing in front of an office building
Negative Prompt
blurry, cropped, ugly
Prompt
A whimsical 3D alcohol ink portrait of a miniature q1s woman mermaid nestled in a giant seashell. She has a shimmering fish tail adorned with intricate scales in various shades of blue and turquoise. She wears a top made of tiny seashells and pearls. Surrounding her are small, bioluminescent jellyfish, adding a magical glow to the scene. The lighting creates a dreamy, underwater atmosphere that captures the essence of oceanic wonder and enchantment.
Negative Prompt
blurry, cropped, ugly
Prompt
a photo of a historical q1s woman marble statue in a grand bathroom
Negative Prompt
blurry, cropped, ugly
Prompt
A captivating watercolor portrayal of a q1s woman. Her eyes are the focal point. The vibrant color palette features bright red, deep green, and pastel beige and white, creating a striking contrast. The fluid, free-flowing brushstrokes imbue the artwork with movement and emotion. The background is an abstract tapestry of color, with splashes of the same hues, adding depth and dimension to the portrait. Painting, illustration.
Negative Prompt
blurry, cropped, ugly
Prompt
a photo of a q1s woman in a hoodie and skirt on the beach
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: 6
  • Training steps: 4400
  • Learning rate: 0.0001
  • Max grad norm: 1.0
  • Effective batch size: 3
    • Micro-batch size: 1
    • Gradient accumulation steps: 3
    • Number of GPUs: 1
  • Prediction type: flow-matching (flux parameters=['flux_schedule_auto_shift', 'shift=0.0', 'flux_guidance_value=1.0', 'flux_attention_masked_training'])
  • Rescaled betas zero SNR: False
  • Optimizer: soap
  • Precision: Pure BF16
  • Quantised: Yes: int8-quanto
  • 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

q1sV8-1024

  • Repeats: 0
  • Total number of images: 15
  • Total number of aspect buckets: 1
  • Resolution: 1.048576 megapixels
  • Cropped: True
  • Crop style: center
  • Crop aspect: square
  • Used for regularisation data: No

q1sV8-512

  • Repeats: 0
  • Total number of images: 19
  • Total number of aspect buckets: 1
  • Resolution: 0.262144 megapixels
  • Cropped: True
  • Crop style: center
  • Crop aspect: square
  • Used for regularisation data: No

pseudo-camera-10k-flux-1024-reg

  • Repeats: 0
  • Total number of images: 1000
  • Total number of aspect buckets: 1
  • Resolution: 1.048576 megapixels
  • Cropped: True
  • Crop style: center
  • Crop aspect: square
  • Used for regularisation data: Yes

pseudo-camera-10k-flux-512-reg

  • Repeats: 0
  • Total number of images: 1000
  • Total number of aspect buckets: 1
  • Resolution: 0.262144 megapixels
  • Cropped: True
  • Crop style: center
  • Crop aspect: square
  • Used for regularisation data: Yes

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 of a q1s woman in a hoodie and skirt on the beach"

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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