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app.py

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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()

requirements.txt

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+fastapi
+uvicorn
+torch
+diffusers
+transformers>=4.22.0
+accelerate
+Pillow  # For handling images
+ftfy  # Fixes text issues, required for tokenization
+scipy  # For certain image processing operations