Create app.py

app.py

@@ -0,0 +1,44 @@
+import os
+import gradio as gr
+from transformers import pipeline
+from pytube import YouTube
+
+
+pipe = pipeline(model="irena/whisper-small-sv-SE") 
+
+
+def yt(link):
+    yt = YouTube(link)
+    stream = yt.streams.filter(only_audio=True)[0]
+    stream.download(filename="audio.mp3")
+    text = pipe("audio.mp3")["text"]
+    return text
+
+def transcribe(audio):
+    text = pipe(audio)["text"]
+    return text
+
+demo = gr.Blocks()
+
+
+iface = gr.Interface(
+    fn=transcribe, 
+    inputs=gr.Audio(source="microphone", type="filepath"), 
+    outputs="text",
+    title="Whisper Small Swedish-Microphone",
+    description="Realtime demo for Swedish speech recognition using a fine-tuned Whisper small model. An audio for recognize.",
+)
+
+yt = gr.Interface(
+    fn=yt,
+    inputs=[gr.inputs.Textbox(lines=1, label="Youtube URL")],
+    outputs=["html", "text"],
+    title="Whisper Small Swedish-Youtube",
+    description="Realtime demo for Swedish speech recognition using a fine-tuned Whisper small model. A Youtube URL for recognize."
+
+)
+
+with demo:
+    gr.TabbedInterface([iface, yt], ["Transcribe Audio", "Transcribe YouTube"])
+
+demo.launch(enable_queue=True)