Create app.py

creating app.py

app.py

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+import torchaudio
+from audiocraft.models import AudioGen
+from audiocraft.data.audio import audio_write
+
+model = AudioGen.get_pretrained('facebook/audiogen-medium')
+model.set_generation_params(duration=5)  # generate 8 seconds.
+wav = model.generate_unconditional(4)    # generates 4 unconditional audio samples
+descriptions = ['dog barking', 'sirenes of an emergency vehicule', 'footsteps in a corridor']
+wav = model.generate(descriptions)  # generates 3 samples.
+
+for idx, one_wav in enumerate(wav):
+    # Will save under {idx}.wav, with loudness normalization at -14 db LUFS.
+    audio_write(f'{idx}', one_wav.cpu(), model.sample_rate, strategy="loudness", loudness_compressor=True)