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import torch
from diffusers import DiffusionPipeline
import gradio as gr
generator = DiffusionPipeline.from_pretrained("CompVis/ldm-text2im-large-256")
# move to GPU if available
if torch.cuda.is_available():
generator = generator.to("cuda")
def generate(prompts):
images = generator(list(prompts)).images
return [images]
demo = gr.Interface(generate,
"textbox",
"image",
batch=True,
max_batch_size=4 # Set the batch size based on your CPU/GPU memory
).queue()
if __name__ == "__main__":
demo.launch()
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