π¨ LoRA text2image fine-tuning - Oil Canvas Style
π Model Description
This model is a fine-tuned version of the Stable Diffusion v1.5 model using Low-Rank Adaptation (LoRA) techniques to generate images in an oil canvas painting style, specifically focusing on the Impressionism genre. The model is designed to produce vibrant, brushstroke-rich images with a joyful and community-focused theme.
π Model Details
- Base Model: Stable Diffusion v1.5 (
runwayml/stable-diffusion-v1-5
) - Fine-Tuning Method: LoRA (Low-Rank Adaptation)
- Training Data: Custom oil canvas style dataset collected from Kaggle, focused on Impressionism artworks (
Eunju2834/img_captioning_oilcanvas_style
,Eunju2834/oil_impressionism_style
) - Captioning Method: BLIP-2 model used to generate image captions for the dataset
- Training Configuration:
- Epochs: 20
- Batch Size: 1
- Learning Rate: 1e-4
- Scheduler: Cosine
- Seed: 2024
π Usage
from diffusers import StableDiffusionPipeline
import torch
model_path = 'Eunju2834/LoRA_oilcanvas_style'
pipe = StableDiffusionPipeline.from_pretrained('runwayml/stable-diffusion-v1-5', torch_dtype=torch.float16, use_auth_token=True)
pipe.unet.load_attn_procs(model_path)
pipe.to('cuda')
prompt = '''(Oil Painting: 1.1), (Impressionism: 1.2), (oil painting with brush strokes: 1.2),
Park stroll, joyful atmosphere, laughter-filled time, playful dogs, vibrant park scene,
cheerful interactions, happy pet owners, heartwarming moments, vibrant community vibes'''
neg_prompt = '''FastNegativeV2, (bad-artist:1.0), (worst quality, low quality:1.4),
(watermark), error, missing fingers, extra digit, cropped, normal quality, blurry'''
image = pipe(prompt, negative_prompt=neg_prompt, num_inference_steps=30, guidance_scale=7.5).images[0]
image.save('oil_impressionism_park_stroll.png')
πΌοΈ Example Results
The model generates images like the ones below, showcasing an oil painting style with vibrant colors and Impressionist influences.
β οΈ Limitations and Biases
- The model is optimized for oil canvas style images and may not generalize well to other artistic styles.
- Potential biases may exist due to the specific nature of the training dataset (e.g., Impressionism artworks).
π License
CreativeML Open RAIL-M
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Model tree for Eunju2834/LoRA_oilcanvas_style
Base model
runwayml/stable-diffusion-v1-5