Update app.py

app.py

@@ -1,3 +1,4 @@
+
 import torch
 from diffusers import DiffusionPipeline, DPMSolverMultistepScheduler
 from diffusers.utils import export_to_video
@@ -16,17 +17,20 @@ if st.button("Generate Video"):
         st.warning("Please upgrade 'accelerate' to version 0.17.0 or higher for CPU offloading.")
     else:
         with st.spinner("Generating video..."):
-            # ... (Your model loading code)
+            # Define the pipeline for image generation
+            pipe = DiffusionPipeline.from_pretrained("damo-vilab/text-to-video-ms-1.7b", 
+                                                 torch_dtype=torch.float16,                                                 variant="fp16",                                                 device="cpu") 
+            pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
+            pipe.enable_model_cpu_offload()  
 
+            # Generate video frames
             video_frames = pipe(prompt, num_inference_steps=25).frames  
 
-            # ... (Your potential reshaping code)
-
-            # Create dummy frames for testing 
+            # Create dummy frames for testing (replace with actual manipulation later)
             dummy_frames = [np.ones((256, 256, 3), dtype=np.uint8) for _ in range(20)]  
 
-            # Replace with your actual export logic
+            # Export to video
             video_path = export_to_video(dummy_frames)
 
             # Display the video in the Streamlit app  
-            st.video(video_path)  
+            st.video(video_path)