Upload app.py

app.py

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+import gradio as gr
+import torch
+from transformers import pipeline
+
+# Load Whisper small pipeline
+device = 0 if torch.cuda.is_available() else -1
+asr = pipeline(
+    "automatic-speech-recognition",
+    model="openai/whisper-small",
+    chunk_length_s=30,
+    device=device,
+)
+
+def transcribe(audio):
+    if audio is None:
+        return "Please upload or record audio"
+    text = asr(audio)["text"]
+    return text
+
+demo = gr.Interface(
+    fn=transcribe,
+    inputs=gr.Audio(sources=["microphone", "upload"], type="filepath"),
+    outputs="text",
+    title="Whisper Small ASR",
+    description="Upload or record audio and get text transcription with OpenAI Whisper Small."
+)
+
+if __name__ == "__main__":
+    demo.launch()