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--- |
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tags: |
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- flux |
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- stable-diffusion |
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- text-to-image |
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- lora |
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- impressionism |
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library_name: diffusers |
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pipeline_tag: text-to-image |
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--- |
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# Flux Impressionism LoRA v1 |
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This is a LoRA fine-tuning of the FLUX.1 model trained on a curated dataset of impressionist paintings from WikiArt. |
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## Dataset |
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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: |
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- Landscapes: 300 images (30%) |
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- Portraits: 300 images (30%) |
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- Urban Scenes: 200 images (20%) |
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- Still Life: 200 images (20%) |
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## Model Details |
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- Base Model: [FLUX.1](https://huggingface.co/black-forest-labs/FLUX.1-dev) |
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- LoRA Rank: 16 |
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- Training Steps: 2000 |
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- Resolution: 512-1024px |
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## Usage |
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```python |
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from diffusers import StableDiffusionPipeline |
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import torch |
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model_id = "black-forest-labs/FLUX.1-dev" |
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lora_model_path = "dolphinium/flux_1_dev_wikiart_impressionism" |
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pipe = StableDiffusionPipeline.from_pretrained( |
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model_id, |
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torch_dtype=torch.float16 |
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).to("cuda") |
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# Load LoRA weights |
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pipe.unet.load_attn_procs(lora_model_path) |
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# Generate image |
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prompt = "an impressionist style landscape with rolling hills and autumn trees" |
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image = pipe(prompt).images[0] |
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image.save("impressionist_landscape.png") |
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``` |
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## License |
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This model inherits the license of the base FLUX.1 model and the WikiArt dataset. |
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