Initial commit

app.py

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+from pytube import YouTube
+from transformers import pipeline
+import gradio as gr
+import os
+
+model = pipeline(model="renesteeman/whisper-base-dutch-25")
+
+def get_audio(url):
+  yt = YouTube(url)
+  video = yt.streams.filter(only_audio=True).first()
+  out_file=video.download(output_path=".")
+  base, ext = os.path.splitext(out_file)
+  new_file = base+'.mp3'
+  os.rename(out_file, new_file)
+  a = new_file
+  return a
+
+def get_text(url):
+#   result = model.transcribe(get_audio(url))
+#   return result['text'].strip()
+    text = model(get_audio(url))["text"]
+    return text
+
+# For Local usage
+# print(get_text("https://www.youtube.com/shorts/KvgkcQMCq44"))
+
+iface = gr.Interface(
+    fn=get_text, 
+    inputs="text", 
+    outputs="text",
+    title="Whisper Small Dutch",
+    description="Realtime demo for Dutch speech recognition using a fine-tuned Whisper small model.",
+)
+
+iface.launch()

requirements.txt

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+torch
+transformers
+pytube