metadata
tags:
- flux
- stable-diffusion
- text-to-image
- lora
- flux dev
- diffusers
- impressionism
library_name: diffusers
pipeline_tag: text-to-image
base_model: black-forest-labs/FLUX.1-dev
widget:
- text: >-
An impressionist painting portrays a vast landscape with gently rolling
hills under a radiant sky. Clusters of autumn trees dot the scene,
rendered with loose, expressive brushstrokes and a palette of warm
oranges, deep greens, and soft blues, creating a sense of tranquil,
natural beauty
output:
url: images/example_jl6x0209w.png
FLUX.1-dev Impressionism fine-tuning with LoRA
This is a LoRA fine-tuning of the FLUX.1 model trained on a curated dataset of impressionist paintings from WikiArt.
Dataset
The model was trained on the WikiArt Impressionism Curated Dataset, which contains 1,000 high-quality Impressionist paintings with the following distribution:
- Landscapes: 300 images (30%)
- Portraits: 300 images (30%)
- Urban Scenes: 200 images (20%)
- Still Life: 200 images (20%)
Model Details
- Base Model: FLUX.1
- LoRA Rank: 16
- Training Steps: 2000
- Resolution: 512-1024px
Usage
from diffusers import StableDiffusionPipeline
import torch
model_id = "black-forest-labs/FLUX.1-dev"
lora_model_path = "dolphinium/FLUX.1-dev-wikiart-impressionism"
pipe = StableDiffusionPipeline.from_pretrained(
model_id,
torch_dtype=torch.float16
).to("cuda")
# Load LoRA weights
pipe.unet.load_attn_procs(lora_model_path)
# Generate image
prompt = "an impressionist style landscape with rolling hills and autumn trees"
image = pipe(prompt).images[0]
image.save("impressionist_landscape.png")
License
This model inherits the license of the base FLUX.1 model and the WikiArt dataset.