Create app.py

app.py

@@ -0,0 +1,25 @@
+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()