Create app.py

app.py

@@ -0,0 +1,26 @@
+import os
+import gradio as gr
+from transformers import pipeline
+from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor
+
+
+MODEL_ID = "jonatasgrosman/wav2vec2-large-xlsr-53-german"
+
+pipeline = pipeline(task="automatic-speech-recognition", model="jonatasgrosman/wav2vec2-large-xlsr-53-german")
+#pipeline = pipeline(task="automatic-speech-recognition", model="openai/whisper-large")
+
+def transcribe(audio_path : str) -> str:
+    transcription = pipeline(audio_path)
+    return transcription
+
+
+demo = gr.Interface(
+    fn=transcribe,
+    #inputs="microphone",
+    inputs=gr.inputs.Audio(label="Upload audio file", type="filepath"),
+    outputs="text"
+)
+
+
+if __name__ == "__main__":
+    demo.launch()