gradio/demo/diffusers_with_batching/run.py
aliabid94 9b42ba8f10
Update guides esp plots (#8907)
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Co-authored-by: Ali Abid <aliabid94@gmail.com>
Co-authored-by: gradio-pr-bot <gradio-pr-bot@users.noreply.github.com>
Co-authored-by: Ali Abdalla <ali.si3luwa@gmail.com>
2024-07-29 22:08:51 -07:00

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Python

import torch
from diffusers import DiffusionPipeline # type: ignore
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 # type: ignore
return [images]
demo = gr.Interface(generate,
"textbox",
"image",
batch=True,
max_batch_size=4 # Set the batch size based on your CPU/GPU memory
)
if __name__ == "__main__":
demo.launch()