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RareConcepts/Flux.1-Dev-DomoKun

sourceHugging Faceotherupdated 2y agoView on Hugging Face
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flux-domokun

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:

<Gallery />

The text encoder was not trained. You may reuse the base model text encoder for inference.

Training settings

  • —Training epochs: 0
  • —Training steps: 100
  • —Learning rate: 0.0002
  • —Effective batch size: 9
  • —Micro-batch size: 3
  • —Gradient accumulation steps: 1
  • —Number of GPUs: 3
  • —Prediction type: flow-matching
  • —Rescaled betas zero SNR: False
  • —Optimizer: bnb-lion8bit
  • —Precision: Pure BF16
  • —Quantised: Yes: nf4-bnb
  • —Xformers: Not used
  • —LyCORIS Config:
json
{
    "bypass_mode": true,
    "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

domokun-uncropped-512

  • —Repeats: 10
  • —Total number of images: ~36
  • —Total number of aspect buckets: 7
  • —Resolution: 0.262144 megapixels
  • —Cropped: False
  • —Crop style: None
  • —Crop aspect: None

domokun-cropped-512

  • —Repeats: 10
  • —Total number of images: ~36
  • —Total number of aspect buckets: 7
  • —Resolution: 0.262144 megapixels
  • —Cropped: False
  • —Crop style: None
  • —Crop aspect: None

Inference

python
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")