Upload app.py

app.py

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+import torch
+from transformers import pipeline
+import gradio as gr
+
+MODEL_NAME = "JackismyShephard/whisper-medium.en-finetuned-gtzan"
+
+device = 0 if torch.cuda.is_available() else "cpu"
+
+pipe = pipeline(
+    task="audio-classification",
+    model=MODEL_NAME,
+    device=device,
+)
+
+def classify_audio(filepath):
+    preds = pipe(filepath, top_k = 10)
+    outputs = {}
+    for p in preds:
+        outputs[p["label"]] = p["score"]
+    return outputs
+
+demo = gr.Interface(
+    fn=classify_audio,
+    inputs= gr.Audio(label="Audio file", type="filepath"),
+    outputs=gr.Label(),
+    title="Music Genre Classification",
+    description=(
+        "Classify long-form audio or microphone inputs with the click of a button! Demo uses the"
+        f" checkpoint [{MODEL_NAME}](https://huggingface.co/{MODEL_NAME}) and 🤗 Transformers to classify audio files"
+        " of arbitrary length."
+    ),
+    examples="./examples",
+    cache_examples=True,
+    allow_flagging="never",
+)
+
+demo.launch()