---
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
---

# 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](https://huggingface.co/datasets/dolphinium/wikiart-impressionism-curated), 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](https://huggingface.co/black-forest-labs/FLUX.1-dev)
- LoRA Rank: 16
- Training Steps: 2000
- Resolution: 512-1024px

## Usage

```python
from diffusers import StableDiffusionPipeline
import torch

model_id = "black-forest-labs/FLUX.1-dev"
lora_model_path = "dolphinium/FLUX.1-dev-wikiart-impressionism-v2"

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.