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license: cc-by-4.0 |
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## Usage |
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The model can be used directly (without a language model) as follows: |
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```python |
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from transformers import Wav2Vec2Processor, Wav2Vec2ForCTC |
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import torch |
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import torchaudio |
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# load model and processor |
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processor = Wav2Vec2Processor.from_pretrained("ivangtorre/wav2vec2-xls-r-300m-quechua") |
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model = Wav2Vec2ForCTC.from_pretrained("ivangtorre/wav2vec2-xls-r-300m-quechua") |
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# load dummy dataset and read soundfiles |
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file = torchaudio.load("quechua000573.wav") |
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# retrieve logits |
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logits = model(file[0]).logits |
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# take argmax and decode |
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predicted_ids = torch.argmax(logits, dim=-1) |
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transcription = processor.batch_decode(predicted_ids) |
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print("HF prediction: ", transcription) |
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``` |
