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from model import DID_Model
import torch
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
aud_path = r"uploads\L.wav"
wave2vec_model_path = r"model_snapshots\wav2vec2_model.pth"
model_path = r"model_snapshots\Marathi_Model_Snapshot.pth"
if __name__ == "__main__":
# Load the Wav2Vec 2.0 model from torchaudio pipelines
# Load custom dialect identification model
model = DID_Model()
model.load_weights(model_path, wave2vec_model_path )
# Predict dialect
predicted_dialect = model.predict_dialect(aud_path) #
print("Predicted Dialect:", predicted_dialect)
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