Instructions to use Jinstudio/VibeVoice-AcousticTokenizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jinstudio/VibeVoice-AcousticTokenizer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Jinstudio/VibeVoice-AcousticTokenizer")# Load model directly from transformers import AutoFeatureExtractor, AutoModel extractor = AutoFeatureExtractor.from_pretrained("Jinstudio/VibeVoice-AcousticTokenizer") model = AutoModel.from_pretrained("Jinstudio/VibeVoice-AcousticTokenizer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 274 Bytes
6c9b2eb | 1 2 3 4 5 6 7 8 9 10 11 12 | {
"eps": 1e-06,
"feature_extractor_type": "VibeVoiceAcousticTokenizerFeatureExtractor",
"feature_size": 1,
"normalize_audio": true,
"padding_side": "right",
"padding_value": 0.0,
"return_attention_mask": true,
"sampling_rate": 24000,
"target_dB_FS": -25
}
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