simpletuner-lora
This is a LyCORIS adapter derived from black-forest-labs/FLUX.1-dev.
The main validation prompt used during training was:
The building exhibits a minimalist architectural approach featuring a stark, white cubic form. Sharp, clean lines define its structure, enhancing a geometric precision. The facade is punctuated by rectangular windows and openings, interspersed asymmetrically. The smooth white stucco finish reflects natural light, creating a play of light and shadow that enhances the purity of its form. Surrounded by a similarly white, flat-roofed wall that delineates the boundary without detracting from the building’s monolithic appearance, the surrounding environment features some neighboring residences with tiled roofs and contemporary designs, but the focus remains on the striking simplicity and modern aesthetics of the cube structure against a clear blue sky.
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:
The text encoder was not trained. You may reuse the base model text encoder for inference.
Training settings
- Training epochs: 2
- Training steps: 1000
- 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
- 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
my-dataset-1024
- Repeats: 1
- Total number of images: 209
- Total number of aspect buckets: 4
- Resolution: 1.048576 megapixels
- Cropped: False
- Crop style: None
- Crop aspect: None
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 = "The building exhibits a minimalist architectural approach featuring a stark, white cubic form. Sharp, clean lines define its structure, enhancing a geometric precision. The facade is punctuated by rectangular windows and openings, interspersed asymmetrically. The smooth white stucco finish reflects natural light, creating a play of light and shadow that enhances the purity of its form. Surrounded by a similarly white, flat-roofed wall that delineates the boundary without detracting from the building’s monolithic appearance, the surrounding environment features some neighboring residences with tiled roofs and contemporary designs, but the focus remains on the striking simplicity and modern aesthetics of the cube structure against a clear blue sky."
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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Model tree for ossaili/simpletuner-lora
Base model
black-forest-labs/FLUX.1-dev