Update app.py

app.py

@@ -1,6 +1,30 @@
-from transformers import pipeline
-generator = pipeline("text-generation", model="gpt2")
-prompt = "Once upon a time, in a galaxy far, far away"
-generated_text = generator(prompt, max_length=100, num_return_sequences=3)
+import torch
+from diffusers import DiffusionPipeline, DPMSolverMultistepScheduler
+from diffusers.utils import export_to_video
+import streamlit as st
 
-print(generated_text)
+# Title and User Input
+st.title("Text-to-Video with Streamlit")
+prompt = st.text_input("Enter your text prompt:", "Spiderman is surfing")
+
+# Button to trigger generation
+if st.button("Generate Video"):
+
+    # Ensure you have 'accelerate' version 0.17.0 or higher (see previous explanation)
+    import accelerate
+    if accelerate.__version__ < "0.17.0":
+        st.warning("Please upgrade 'accelerate' to version 0.17.0 or higher for CPU offloading.")
+    else:
+        with st.spinner("Generating video..."):
+            pipe = DiffusionPipeline.from_pretrained("cerspense/zeroscope_v2_576w", 
+                                         torch_dtype=torch.float16, 
+                                         variant="fp16",
+                                         device="cpu") # Force CPU usage
+            pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
+            pipe.enable_model_cpu_offload()  # Assuming 'accelerate' is updated  
+
+            video_frames = pipe(prompt, num_inference_steps=25).frames
+            video_path = export_to_video(video_frames)
+
+            # Display the video in the Streamlit app
+            st.video(video_path)