revert 17 nov

app.py

@@ -17,8 +17,12 @@ from huggingface_hub import hf_hub_download
 
 #gradio.helpers.CACHED_FOLDER = '/data/cache'
 
+# Load the pipeline with authentication token
 pipe = StableVideoDiffusionPipeline.from_pretrained(
-    "stabilityai/stable-video-diffusion-img2vid-xt", torch_dtype=torch.float16, variant="fp16"
+    "multimodalart/stable-video-diffusion",
+    torch_dtype=torch.float16,
+    variant="fp16",
+    use_auth_token=os.getenv("HUGGINGFACE_TOKEN")  # Fetch the token from the environment variable
 )
 pipe.to("cuda")
 #pipe.unet = torch.compile(pipe.unet, mode="reduce-overhead", fullgraph=True)
@@ -43,7 +47,7 @@ def sample(
     if image.mode == "RGBA":
         image = image.convert("RGB")
         
-    if(randomize_seed):
+    if randomize_seed:
         seed = random.randint(0, max_64_bit_int)
     generator = torch.manual_seed(seed)
     
@@ -105,6 +109,23 @@ with gr.Blocks() as demo:
       
   image.upload(fn=resize_image, inputs=image, outputs=image, queue=False)
   generate_btn.click(fn=sample, inputs=[image, seed, randomize_seed, motion_bucket_id, fps_id], outputs=[video, seed], api_name="video")
+  gr.Examples(
+    examples=[
+        "images/blink_meme.png",
+        "images/confused2_meme.png",
+        "images/disaster_meme.png",
+        "images/distracted_meme.png",
+        "images/hide_meme.png",
+        "images/nazare_meme.png",
+        "images/success_meme.png",
+        "images/willy_meme.png",
+        "images/wink_meme.png"
+    ],
+    inputs=image,
+    outputs=[video, seed],
+    fn=sample,
+    cache_examples="lazy",
+  )
 
 if __name__ == "__main__":
     #demo.queue(max_size=20, api_open=False)