from diffusers import DiffusionPipeline
import argparse

# Parse command line arguments
parser = argparse.ArgumentParser(description='Generate an image using a Hugging Face diffusion model')
parser.add_argument('--model', type=str, default="uisikdag/ddpm-few-shot-art-painting", 
                    help='Hugging Face model name/path')
parser.add_argument('--steps', type=int, default=500, 
                    help='Number of inference steps')
args = parser.parse_args()

# Load the model
generator = DiffusionPipeline.from_pretrained(args.model).to("cuda")

# Generate image
image = generator(num_inference_steps=args.steps).images[0]

# Save the image with model name in the filename
output_filename = f"output_{args.model.split('/')[-1]}.png"
image.save(output_filename)
print(f"Image saved as {output_filename}")