Update app.py

app.py

@@ -4,30 +4,30 @@ from diffusers import DiffusionPipeline, DPMSolverMultistepScheduler
 from diffusers.utils import export_to_video
 
 device = "cuda" if torch.cuda.is_available() else "cpu"
-
+model = gr.Interface("models/cerspense/zeroscope_v2_576w")
 # load pipeline
-pipe = DiffusionPipeline.from_pretrained("cerspense/zeroscope_v2_576w").to(device)
-pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
-if device == "cuda":
+#pipe = DiffusionPipeline.from_pretrained("cerspense/zeroscope_v2_576w").to(device)
+#pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
+#if device == "cuda":
     # optimize for GPU memory
-    pipe.enable_model_cpu_offload()
-else:
-    pass
-pipe.enable_vae_slicing()
+#    pipe.enable_model_cpu_offload()
+#else:
+#    pass
+#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
+    video_frames = model(prompt, num_inference_steps=25, num_frames=20)
     
     # convent to video
-    video_path = export_to_video(video_frames)
-    return video_path
+    #video_path = export_to_video(video_frames)
+    return video_frames
 
 with gr.Blocks() as app:
     inp = gr.Textbox()
     btn = gr.Button()
-    outp = gr.Video()
+    outp = gr.Gallery()
     btn.click(ttv,None,outp)
 app.launch()