create app

app.py

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+from transformers import pipeline
+import gradio as gr
+
+model_id = "mmhamdy/whisper-tiny-finetuned-minds14-en-us"  
+pipe = pipeline("automatic-speech-recognition", model=model_id)
+
+def transcribe_speech(filepath):
+    output = pipe(
+        filepath,
+        max_new_tokens=256,
+        generate_kwargs={
+            "task": "transcribe",
+            "language": "english",
+        }, 
+        chunk_length_s=30,
+        batch_size=8,
+    )
+    return output["text"]
+
+demo = gr.Blocks()
+
+mic_transcribe = gr.Interface(
+    fn=transcribe_speech,
+    inputs=gr.Audio(source="microphone", type="filepath"),
+    outputs=gr.outputs.Textbox(),
+)
+
+file_transcribe = gr.Interface(
+    fn=transcribe_speech,
+    inputs=gr.Audio(source="upload", type="filepath"),
+    outputs=gr.outputs.Textbox(),
+)
+
+with demo:
+    gr.TabbedInterface(
+        [mic_transcribe, file_transcribe],
+        ["Transcribe Microphone", "Transcribe Audio File"],
+    )
+
+demo.launch(debug=True)

requirements.txt

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+transformers
+torch