Create app.py

app.py

@@ -0,0 +1,44 @@
+from transformers import pipeline
+import os
+import gradio as gr
+import torch
+
+#Text to text
+#translator = pipeline(task="translation",
+#                      model="facebook/nllb-200-distilled-600M",
+#                      torch_dtype=torch.bfloat16) 
+#Text to audio
+pipe = pipeline("text-to-speech", model="suno/bark-small",
+                      torch_dtype=torch.bfloat16)
+
+                
+demo = gr.Blocks()
+def transcribe_speech(filepath):
+    if filepath is None:
+        gr.Warning("No text found, please retry.")
+        return ""
+    narrated_text=pipe(filepath)
+    return narrated_text
+    
+mic_transcribe = gr.Interface(
+    fn=transcribe_speech,
+    inputs=gr.Textbox(label="Text",lines=3),
+    outputs="audio",
+    allow_flagging="never")
+
+file_transcribe = gr.Interface(
+    fn=transcribe_speech,
+    inputs=gr.Audio(sources="upload",
+                    type="filepath"),
+    outputs="audio",
+    #outputs=gr.Audio(label="Translated Message"),
+    allow_flagging="never"
+)
+with demo:
+    gr.TabbedInterface(
+        [mic_transcribe],
+        ["Transcribe Microphone"],
+    )
+
+demo.launch(share=True)
+demo.close()