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
| { | |
| "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 | |
| } | |