The main validation prompt used during training was:
This idyllic alpine scene captures a serene lake nestled between lush green hills and towering mountains capped with snow. A wooden chalet, located on a gently sloping hill, overlooks the vibrant turquoise waters of the lake, its spacious balcony offering sweeping views of the breathtaking landscape. The surrounding meadows are dotted with colorful wildflowers, and tall trees line the hillsides, blending harmoniously with the forested mountains in the distance. Beyond the lake, a small village can be seen, framed by majestic peaks that rise sharply against a bright blue sky adorned with fluffy white clouds. The crystal-clear water reflects the sky and the surrounding greenery, enhancing the tranquility of the scene. Every detail, from the texture of the grass to the snow on the distant mountains, is rendered with vibrant clarity, evoking a sense of peace and natural beauty in this picturesque mountain retreat.
Validation settings
CFG: 4.0
CFG Rescale: 0.0
Steps: 20
Sampler: None
Seed: 42
Resolution: 1344x768
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: 14
Training steps: 9000
Learning rate: 8e-05
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: Yes: int8-quanto
Xformers: Not used
LoRA Rank: 64
LoRA Alpha: None
LoRA Dropout: 0.1
LoRA initialisation style: default
Datasets
realistic-16-09-512
Repeats: 10
Total number of images: 14
Total number of aspect buckets: 1
Resolution: 0.262144 megapixels
Cropped: False
Crop style: None
Crop aspect: None
realistic-16-09-1024
Repeats: 10
Total number of images: 14
Total number of aspect buckets: 1
Resolution: 1.048576 megapixels
Cropped: False
Crop style: None
Crop aspect: None
realistic-16-09-512-crop
Repeats: 10
Total number of images: 14
Total number of aspect buckets: 1
Resolution: 0.262144 megapixels
Cropped: True
Crop style: random
Crop aspect: square
realistic-16-09-1024-crop
Repeats: 10
Total number of images: 14
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
model_id = 'black-forest-labs/FLUX.1-dev'
adapter_id = 'datnt114/train-realistic-16-09-v2'
pipeline = DiffusionPipeline.from_pretrained(model_id)
pipeline.load_lora_weights(adapter_id)
prompt = "This idyllic alpine scene captures a serene lake nestled between lush green hills and towering mountains capped with snow. A wooden chalet, located on a gently sloping hill, overlooks the vibrant turquoise waters of the lake, its spacious balcony offering sweeping views of the breathtaking landscape. The surrounding meadows are dotted with colorful wildflowers, and tall trees line the hillsides, blending harmoniously with the forested mountains in the distance. Beyond the lake, a small village can be seen, framed by majestic peaks that rise sharply against a bright blue sky adorned with fluffy white clouds. The crystal-clear water reflects the sky and the surrounding greenery, enhancing the tranquility of the scene. Every detail, from the texture of the grass to the snow on the distant mountains, is rendered with vibrant clarity, evoking a sense of peace and natural beauty in this picturesque mountain retreat."
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=1344,
height=768,
guidance_scale=4.0,
).images[0]
image.save("output.png", format="PNG")