Update app.py

app.py

@@ -1,21 +1,21 @@
 import streamlit as st
 import torch
-from diffusers import WanPipeline
+from diffusers import StableVideoDiffusionPipeline
 from diffusers.utils import export_to_video
 
-# Load the Wan2.1 text-to-video pipeline (1.3B version) with half-precision weights
+# Load the video generation pipeline
 st.write("Loading model... (first run may take a few minutes)")
 
-model_id = "Wan-AI/Wan2.1-T2V-1.3B-Diffusers"
-pipe = WanPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
+model_id = "stabilityai/stable-video-diffusion-img2vid"
+pipe = StableVideoDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
 
-st.title("Wan2.1 Text-to-Video Generator")
+st.title("Text-to-Video Generator")
 prompt = st.text_input("Enter a text prompt for the video:")
 frames = st.slider("Number of frames (video length)", min_value=8, max_value=81, value=24)
 
 if st.button("Generate Video") and prompt:
     with st.spinner("Generating video... this may take a while on CPU"):
-        result = pipe(prompt=prompt, height=480, width=832, num_frames=frames, num_inference_steps=20)
+        result = pipe(prompt=prompt, num_frames=frames, num_inference_steps=20)
         video_frames = result.frames  # List of PIL images
         export_to_video(video_frames, "output.mp4", fps=8)