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app.py

@@ -81,20 +81,6 @@ def generate_video_gpu(
     guidance_scale,
     flow_shift,
     embedded_guidance_scale
-):
-    return None
-
-@spaces.GPU(duration=120)
-def generate_video_gpu2(
-    model,
-    prompt,
-    resolution,
-    video_length,
-    seed,
-    num_inference_steps,
-    guidance_scale,
-    flow_shift,
-    embedded_guidance_scale
 ):
     print("generate_video_gpu (prompt: " + prompt + ")")
     if torch.cuda.device_count() == 0:
@@ -145,7 +131,8 @@ def create_demo(model_path):
                     <p style="background-color: red;"><big><big><big><b>⚠️To use <i>Hunyuan Video</i>, <a href="https://huggingface.co/spaces/Fabrice-TIERCELIN/HunyuanVideo?duplicate=true">duplicate this space</a> and set a GPU with 80 GB VRAM.</b>
     
                     You can't use <i>Hunyuan Video</i> directly here because this space runs on a CPU, which is not enough for <i>Hunyuan Video</i>. Please provide <a href="https://huggingface.co/spaces/Fabrice-TIERCELIN/HunyuanVideo/discussions/new">feedback</a> if you have issues.
-                    </big></big></big></p>
+                    </big></big></big></p><br/><br/>
+                    <p style="background-color: green;"><big>The space has been successfully deployed on A100 space. Then we can discuss about the quality of the generation.</big></p>
                     """)
         gr.Markdown("# Hunyuan Video Generation")