Create geeee

geeee

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+import torch
+import streamlit as st
+from diffusers import CogVideoXPipeline
+from diffusers.utils import export_to_video
+
+st.title("CogVideoX Video Generation on CPU")
+
+# Your prompt
+prompt = "A panda, dressed in a small, red jacket and a tiny hat, sits on a wooden stool in a serene bamboo forest. The panda's fluffy paws strum a miniature acoustic guitar, producing soft, melodic tunes. Nearby, a few other pandas gather, watching curiously and some clapping in rhythm. Sunlight filters through the tall bamboo, casting a gentle glow on the scene. The panda's face is expressive, showing concentration and joy as it plays. The background includes a small, flowing stream and vibrant green foliage, enhancing the peaceful and magical atmosphere of this unique musical performance."
+
+if st.button("Generate Video"):
+    with st.spinner("Generating video on CPU..."):
+        # Load the model and force it to run on CPU
+        pipe = CogVideoXPipeline.from_pretrained(
+            "THUDM/CogVideoX-2b",
+            torch_dtype=torch.float32  # Use float32 for CPU
+        )
+
+        # Ensure model uses CPU
+        pipe.to("cpu")
+
+        # VAE optimizations
+        pipe.vae.enable_slicing()
+        pipe.vae.enable_tiling()
+
+        # Generate the video
+        video = pipe(
+            prompt=prompt,
+            num_videos_per_prompt=1,
+            num_inference_steps=50,
+            num_frames=49,
+            guidance_scale=6,
+            generator=torch.manual_seed(42),  # Use manual_seed for CPU
+        ).frames[0]
+
+        # Export video
+        export_to_video(video, "output.mp4", fps=8)
+        
+        # Show the video in Streamlit
+        st.video("output.mp4")
+
+        st.success("Video generated successfully on CPU!")