metadata
license: other
base_model: black-forest-labs/FLUX.1-dev
tags:
- flux
- flux-diffusers
- text-to-image
- diffusers
- simpletuner
- lora
- template:sd-lora
inference: true
widget:
- text: unconditional (blank prompt)
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/image_0_0.png
- text: >-
night landscape, full moon, starry sky, mountain silhouette, glowing moon,
fireflies, illuminated grass, forest trees, blue tone, serene atmosphere,
dreamy scene, outdoor wilderness, natural beauty, twilight, nocturnal
environment, magical ambiance, night photography, moonlit field, peaceful
setting, lush greenery
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/image_1_0.png
- text: >-
Dense forest, ancient tree, wooden bridge, moss-covered, flowing stream,
mystical atmosphere, high resolution, balanced composition, green foliage,
misty background, realistic photography, soft natural light, lush
greenery, nature scenery, serene, tranquil mood, detailed texture, vibrant
greens, forest pathway, overgrown.
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/image_2_0.png
- text: >-
cabin in the woods, misty forest, realistic photography, centered
composition, high resolution, dark color palette, soft evening light,
front view, wooden texture, eerie atmosphere, warm interior light, serene
setting, reflective water surface, overcast sky, rustic house, forested
landscape, dim lighting, reflective puddles, wet ground, cozy yet
mysterious ambiance
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/image_3_0.png
- text: >-
An illustration of a serene landscape at night, moonlit mountain scene,
tall pine trees on a small island, snow-capped mountains in the
background, still lake reflecting trees and full moon, cloud-speckled sky
dotted with stars, soft ambient lighting, primary color tones of blue and
white, ambient and tranquil atmosphere, high resolution, extremely
detailed.
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/image_4_0.png
simpletuner-lora
This is a standard PEFT LoRA derived from black-forest-labs/FLUX.1-dev.
The main validation prompt used during training was:
An illustration of a serene landscape at night, moonlit mountain scene, tall pine trees on a small island, snow-capped mountains in the background, still lake reflecting trees and full moon, cloud-speckled sky dotted with stars, soft ambient lighting, primary color tones of blue and white, ambient and tranquil atmosphere, high resolution, extremely detailed.
Validation settings
- CFG:
3.0
- 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: 9
- Training steps: 10000
- 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: bf16
- Quantised: Yes: int8-quanto
- Xformers: Not used
- LoRA Rank: 16
- LoRA Alpha: 16.0
- LoRA Dropout: 0.1
- LoRA initialisation style: default
Datasets
pseudo-natural-booru-flux
- Repeats: 0
- Total number of images: 1089
- Total number of aspect buckets: 1
- Resolution: 1.048576 megapixels
- Cropped: True
- Crop style: center
- Crop aspect: square
Inference
import torch
from diffusers import DiffusionPipeline
model_id = 'black-forest-labs/FLUX.1-dev'
adapter_id = 'datnt114/simpletuner-lora'
pipeline = DiffusionPipeline.from_pretrained(model_id)
pipeline.load_lora_weights(adapter_id)
prompt = "An illustration of a serene landscape at night, moonlit mountain scene, tall pine trees on a small island, snow-capped mountains in the background, still lake reflecting trees and full moon, cloud-speckled sky dotted with stars, soft ambient lighting, primary color tones of blue and white, ambient and tranquil atmosphere, high resolution, extremely detailed."
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=3.0,
).images[0]
image.save("output.png", format="PNG")