Instructions to use bezzam/VibeVoice-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bezzam/VibeVoice-7B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="bezzam/VibeVoice-7B")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTextToWaveform processor = AutoProcessor.from_pretrained("bezzam/VibeVoice-7B") model = AutoModelForTextToWaveform.from_pretrained("bezzam/VibeVoice-7B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 300 Bytes
89a427b | 1 2 3 4 5 6 7 8 9 10 11 12 13 | {
"eps": 1e-06,
"feature_extractor_type": "VibeVoiceFeatureExtractor",
"feature_size": 1,
"normalize_audio": true,
"padding_side": "right",
"padding_value": 0.0,
"processor_class": "VibeVoiceProcessor",
"return_attention_mask": true,
"sampling_rate": 24000,
"target_dB_FS": -25
}
|