Update app.py

app.py

@@ -2,7 +2,15 @@ import torch
 from diffusers import DiffusionPipeline, DPMSolverMultistepScheduler
 from diffusers.utils import export_to_video
 import streamlit as st
+from diffusers import UNet2DConditionModel, TextEncoder, VQModel
 
+# Use the default model names here
+unet_model_name = "unet/diffusion_pytorch_model.bin"
+text_encoder_name = "text_encoder/pytorch_model.bin"
+vae_model_name = "vae/diffusion_pytorch_model.bin"
+
+# Create the pipeline or model objects using the default names
+pipeline = UNet2DConditionModel.from_pretrained(unet_model_name)
 # Title and User Input
 st.title("Text-to-Video with Streamlit")
 prompt = st.text_input("Enter your text prompt:", "Spiderman is surfing")