Update markdown language

app.py

@@ -160,7 +160,15 @@ def process_youtube(youtube_address):
 
 with gr.Blocks(title="Audio Fake Detector") as demo:
     with gr.Tab("Individual Processing"):
-        gr.Markdown("# Welcome to Loccus.ai voice cloning detection demo!")
+        gr.Markdown("""# Welcome to Loccus' Authenticity Verification demo!
+        This is a showcase of our solution. It provides a probability of a voice being real or AI-generated. It is designed for the following context:
+        * To detect voice clones
+        * Focus on English and Spanish languages
+        * For short audio samples (3 to 10 seconds)
+        * For audio from digital channels (at 16 kHz or more)
+                    
+        Please test it accordingly. Variations of the above (e.g. a 1 minute audio file of an off-the-shelf TTS voice in Japanese) can compromise the accuracy and performance of the solution. We keep improving the solution adding new features every week.""")
+    
     
 
     
@@ -185,7 +193,7 @@ with gr.Blocks(title="Audio Fake Detector") as demo:
         #v.upload(process_video, inputs=[v], outputs=[text])
 
     with gr.Tab("Batch Processing"):
-        gr.Markdown("# Welcome to Loccus.ai voice cloning detection demo!")
+        gr.Markdown("# Welcome to Loccus' Authenticity Verification demo!")
 
         with gr.Row():
             with gr.Column():

notes.txt

@@ -1,9 +0,0 @@
-https://discuss.huggingface.co/t/embedding-spaces-with-auth-for-public-models-counter-intuitive/32868/2
-
-Hello @EtheE, thank you for your feedback. We have received similar requests in the past, we might implement a solution it in the future. However, we have previously suggested different workarounds depending on the specific use case:
-
-    To hide sensitive source code on Space, you can create a private Space and a second public Space which only loads the private Space using the ‘gr.Interface.load()’ method. This method can load a Space even if it is private. Check more her Gradio Docs 74.
-
-    To hide specific files only, you can create a private dataset/model and use the ‘huggingface_hub’ client to load your dataset/model using the hub token via Space settings.
-
-    You can also use our Inference Endpoints PaaS service which is fully integrated with HF tools and our hub. This service provides a way to deploy a Space as a REST API. You can learn more about it here Inference Endpoints - Hugging Face 47