metadata
license: creativeml-openrail-m
base_model: black-forest-labs/FLUX.1-dev
tags:
- stable-diffusion
- stable-diffusion-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: >-
es_style, two figures embraced, one male: red cap, one female: black
headdress, standing, hands clasped close, greenish background, earthy
tones, muted colors, asymmetrical balance, shadowy harmony, textured
brushwork, high contrast, layered application, melancholic, signature
bottom-right
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/image_1_0.png
- text: >-
es_style, 2 figures (woman: brown dress, child: orange clothing), intimate
embrace, minimal background, muted tones, textured brushwork, loosely
defined, asymmetrical balance, melancholic, signature bottom-left
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/image_2_0.png
- text: >-
es_style, single figure (man: brown suit, red tie), no background detail,
muted tones, asymmetrical balance, textured brushwork, sharp contours,
rhythmic patterns, melancholic, signature bottom-left
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/image_3_0.png
- text: >-
es_style, single female figure, red headband, simple draped fabric,
looking downward, indoor setting, white background, light beige hues, dark
lines, asymmetrical balance, muted tones, sharp contours, dynamic energy,
serene, signature bottom-right
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/image_4_0.png
- text: >-
mp_style, Street scene, 50 figures (many women: colorful dresses, many
men: suits), 23 umbrellas (orange, red, yellow, green), bridge, buildings
background, water, boats, Italian flag, steps, lamps, crowd ascending
descending bridge, signature bottom-left
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/image_5_0.png
lora-Egon-Schiele-Flux
This is a LoRA derived from black-forest-labs/FLUX.1-dev.
The main validation prompt used during training was:
mp_style, Street scene, 50 figures (many women: colorful dresses, many men: suits), 23 umbrellas (orange, red, yellow, green), bridge, buildings background, water, boats, Italian flag, steps, lamps, crowd ascending descending bridge, signature bottom-left
Validation settings
- CFG:
7.5
- CFG Rescale:
0.0
- Steps:
20
- Sampler:
None
- Seed:
42
- Resolution:
512
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: 3
- Training steps: 440
- Learning rate: 0.0004
- 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, stochastic bf16
- Precision: Pure BF16
- Quantised: No
- Xformers: Not used
- LoRA Rank: 64
- LoRA Alpha: None
- LoRA Dropout: 0.1
- LoRA initialisation style: default
Datasets
EgonSchiele
- Repeats: 0
- Total number of images: 122
- Total number of aspect buckets: 1
- Resolution: 1024 px
- 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 = 'davidrd123/lora-Egon-Schiele-Flux'
pipeline = DiffusionPipeline.from_pretrained(model_id)
pipeline.load_lora_weights(adapter_id)
prompt = "mp_style, Street scene, 50 figures (many women: colorful dresses, many men: suits), 23 umbrellas (orange, red, yellow, green), bridge, buildings background, water, boats, Italian flag, steps, lamps, crowd ascending descending bridge, signature bottom-left"
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=512,
height=512,
guidance_scale=7.5,
).images[0]
image.save("output.png", format="PNG")