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import gradio as gr | |
from diffusers import StableDiffusionPipeline | |
import torch | |
from transformers import logging | |
logging.set_verbosity_error() # This suppresses warnings, including cache migration | |
#GPU error | |
from diffusers import StableDiffusionPipeline | |
# Load the model | |
model_id = "MostafaAly/stable-diffusion-finetuned" | |
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16) | |
# Check if CUDA is available and move the model to GPU if it is, otherwise use CPU | |
device = "cuda" if torch.cuda.is_available() else "cpu" | |
pipe.to(device) | |
print(f"Using device: {device}") | |
# Define the function for text-to-image generation | |
def generate_image(prompt): | |
image = pipe(prompt).images[0] | |
return image | |
# Create a Gradio interface | |
interface = gr.Interface( | |
fn=generate_image, | |
inputs=gr.Textbox(label="Enter your prompt"), | |
outputs=gr.Image(label="Generated Image"), | |
) | |
# Launch the interface | |
interface.launch() | |