Create app.py

app.py

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+import gradio as gr
+import torch
+from diffusers import DiffusionPipeline, DPMSolverMultistepScheduler
+from diffusers.utils import export_to_video
+
+# 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()
+def ttv():
+    
+    # generate
+    prompt = "Spiderman is surfing. Darth Vader is also surfing and following Spiderman"
+    video_frames = pipe(prompt, num_inference_steps=25, num_frames=200).frames
+    
+    # convent to video
+    video_path = export_to_video(video_frames)
+    return video_path
+
+with gr.Blocks() as app:
+    inp = gr.Textbox()
+    btn = gr.Button()
+    outp = gr.Video()
+    btn.click(ttv,None,outp)
+app.launch()