Instructions to use jeromeshaiju/VANGOH-LORA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jeromeshaiju/VANGOH-LORA with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("jeromeshaiju/VANGOH-LORA") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
π¨ SDXL LoRA: Van Gogh Style Transformer
This LoRA was fine-tuned on the Stable Diffusion XL (SDXL) Base 1.0 model. It is designed to infuse images with the iconic Post-Impressionist aesthetic of Vincent van Gogh, specifically focusing on his signature swirling brushstrokes, vibrant impasto textures, and emotive color palettes.
π Model Details
- Developer: Jerome Shaiju
- Model Type: LoRA (Low-Rank Adaptation)
- Base Model: SDXL 1.0
- Trigger Word:
vangoh_style - Primary Use Case: Image-to-Image transformations (Style Transfer)
π οΈ Usage Instructions
To get the best results, use a Style Strength (Denoising) of 0.5 - 0.7. If the strength is too high, the facial features might distort; if too low, the brushstrokes won't appear.
Python Code (Diffusers Integration)
from diffusers import AutoPipelineForImage2Image
import torch
# Load Pipeline
pipe = AutoPipelineForImage2Image.from_pretrained(
"stabilityai/stable-diffusion-xl-base-1.0",
torch_dtype=torch.float16
).to("cuda")
# Load your LoRA
pipe.load_lora_weights("jeromeshaiju/VANGOH-LORA", weight_name="vangoh-10.safetensors")
# Run Inference
prompt = "a professional portrait in vangoh_style, cinematic, high detail, masterpiece"
image = pipe(prompt=prompt, image=input_image, strength=0.6).images[0]
image.save("result.png")
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Model tree for jeromeshaiju/VANGOH-LORA
Base model
stabilityai/stable-diffusion-xl-base-1.0