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from diffusers import StableDiffusionPipeline
import torch
# Load the Stable Diffusion 3.5 model
model_id = "stabilityai/stable-diffusion-3.5"
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
pipe.to("cuda")
# Define the path to the LoRA model (since it's in the main directory)
lora_model_path = "lora_model.pth" # Path to the uploaded LoRA model
# Load the LoRA model weights into the pipeline
pipe.load_lora_model(lora_model_path) # Integrate the LoRA weights
# Function to generate an image from a text prompt
def generate_image(prompt):
image = pipe(prompt).images[0]
return image
import gradio as gr
iface = gr.Interface(fn=generate_image, inputs="text", outputs="image")
iface.launch()
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