app.py

import torch
import gradio as gr
from diffusers import DiffusionPipeline, DPMSolverMultistepScheduler
from diffusers.utils import export_to_video

pipeline = DiffusionPipeline.from_pretrained("damo-vilab/text-to-video-ms-1.7b")

def generate_video(prompt):
    # load pipeline
    pipe = DiffusionPipeline.from_pretrained("damo-vilab/text-to-video-ms-1.7b", torch_dtype=torch.float16, variant="fp16")
    pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)

    # optimize for GPU memory
    pipe.enable_model_cpu_offload()
    pipe.enable_vae_slicing()

    # generate
    video_frames = pipe(prompt, num_inference_steps=25, num_frames=200).frames

    # convert to video
    video_path = export_to_video(video_frames)
    return video_path

iface = gr.Interface(fn=generate_video, inputs="text", outputs="file")
iface.launch()