!pip install diffusers transformers
!pip install torch torchvision
!pip install accelerate
#DON't run this code on your labtop. run it on colab!
#it need more than 32 Gb RAM and will take more than 5 GB at your hard
import torch
from diffusers import StableDiffusionPipeline

# Load the model
model_id = "CompVis/stable-diffusion-v1-4"
device = "cuda" if torch.cuda.is_available() else "cpu"
pipe = StableDiffusionPipeline.from_pretrained(model_id)
#Mayhtam Ghanoum

pipe = pipe.to(device)

# Function to generate images
def generate_images(prompt, num_images=1):
    images = []
    for _ in range(num_images):
        with torch.no_grad():
            image = pipe(prompt)["images"][0]
        images.append(image)
    return images

# Example usage
prompt = " " #Put your prompt here
generated_images = generate_images(prompt, num_images=1)

import matplotlib.pyplot as plt
# Display images using Matplotlib
for img in generated_images:
    plt.figure(figsize=(6, 6))
    plt.imshow(img)
    plt.axis("off")
    plt.show()