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--- |
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library_name: transformers |
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license: mit |
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--- |
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# ContentVec |
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The ContentVec model in safetensors format, compatible with HuggingFace Transformers. |
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## Uses |
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To extract features, use the following code: |
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```python |
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from transformers import AutoProcessor, HubertModel |
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import librosa |
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# Load the processor and model |
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processor = AutoProcessor.from_pretrained("safe-models/ContentVec") |
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hubert = HubertModel.from_pretrained("safe-models/ContentVec") |
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# Read the audio |
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audio, sr = librosa.load("test.wav", sr=16000) |
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input_values = processor(audio, sampling_rate=sr, return_tensors="pt").input_values |
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# Get the layer 12 output as the feature |
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feats = hubert(input_values, output_hidden_states=True)["hidden_states"][12] |
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print(f"{feats.shape=}") |
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``` |
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