Hf Token update

app.py

@@ -1,41 +1,37 @@
+import os
 import spaces
 import torch
 import gradio as gr
 from diffusers import StableAudioPipeline
 
-# 1. Load pipeline on CPU first (ZeroGPU pattern)
+# Load model passing token=True to authenticate
 pipe = StableAudioPipeline.from_pretrained(
     "stabilityai/stable-audio-open-1.0", 
-    torch_dtype=torch.float16
+    torch_dtype=torch.float16,
+    token=True  # <--- Reads HF_TOKEN secret automatically
 )
 
-# 2. Decorate the execution function with @spaces.GPU
 @spaces.GPU(duration=60)
 def generate_audio(prompt, negative_prompt, seconds):
-    # Move to GPU dynamically when invoked
     pipe.to("cuda")
-    
     output = pipe(
         prompt=prompt,
         negative_prompt=negative_prompt,
         audio_end_in_s=seconds,
         num_inference_steps=100,
     )
-    
-    # Format output for Gradio (Sample Rate, Audio Array)
     audio_data = output.audios[0].T.cpu().numpy()
     return (44100, audio_data)
 
-# 3. Launch Gradio UI
 demo = gr.Interface(
     fn=generate_audio,
     inputs=[
-        gr.Textbox(label="Prompt", value="128 BPM tech house drum loop with heavy kick and sub bass"),
-        gr.Textbox(label="Negative Prompt", value="low quality, noise, distortion"),
+        gr.Textbox(label="Prompt", value="Heavy metal door slam in an echoing dungeon"),
+        gr.Textbox(label="Negative Prompt", value="low quality, distortion"),
         gr.Slider(minimum=5, maximum=47, value=15, label="Duration (Seconds)")
     ],
-    outputs=gr.Audio(label="Generated Audio"),
-    title="Stable Audio Open Generator"
+    outputs=gr.Audio(label="Generated SFX"),
+    title="Stable Audio Studio"
 )
 
 demo.launch()