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import gradio as gr | |
from diffusers import StableDiffusionPipeline, DPMSolverMultistepScheduler | |
import torch | |
# Load the base model | |
base_model = "stabilityai/stable-diffusion-xl-base-1.0" | |
lora_model = "itsVilen/Mspaint" | |
pipe = StableDiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.float16) | |
pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config) | |
# Load the LoRA weights | |
pipe.load_lora_weights(lora_model) | |
pipe.to("cuda") | |
def generate_image(prompt): | |
try: | |
# Generate an image from the prompt | |
image = pipe(prompt).images[0] | |
return image | |
except Exception as e: | |
return str(e) | |
iface = gr.Interface( | |
fn=generate_image, | |
inputs=gr.Textbox(lines=2, placeholder="Enter your prompt here..."), | |
outputs=gr.Image(type="pil"), | |
title="Text to Image Generation", | |
description="Enter a text prompt and generate an image using the itsVilen/Mspaint model.", | |
) | |
iface.launch() | |