Create app.py

app.py

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+import gradio as gr
+import spaces
+from diffusers import DiffusionPipeline, DPMSolverMultistepScheduler
+from diffusers.utils import export_to_video
+
+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)
+pipe.enable_model_cpu_offload()
+
+@spaces.GPU(duration=250)
+def generate(prompt, num_inference_steps=25):
+    video_frames = pipe(prompt, num_inference_steps).frames
+    video_path = export_to_video(video_frames)
+    return video_path
+
+prompt = gr.Textbox("Enter prompt to generate a video")
+num_inference_steps = gr.Slider(10, 50, value=25)
+
+interface = gr.Interface(
+    generate,
+    inputs=[prompt, num_inference_steps],
+    examples=[["Astronaut riding a horse", 25], ["Darth vader surfing in waves", 20]]
+    outputs="video",
+    cache_examples=False,
+    theme="soft"
+)