Instructions to use Sergey004/VibeVoice-Large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sergey004/VibeVoice-Large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="Sergey004/VibeVoice-Large")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTextToWaveform processor = AutoProcessor.from_pretrained("Sergey004/VibeVoice-Large") model = AutoModelForTextToWaveform.from_pretrained("Sergey004/VibeVoice-Large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 349 Bytes
0f94816 | 1 2 3 4 5 6 7 8 9 10 11 12 13 | {
"processor_class": "VibeVoiceProcessor",
"speech_tok_compress_ratio": 3200,
"db_normalize": true,
"audio_processor": {
"feature_extractor_type": "VibeVoiceTokenizerProcessor",
"sampling_rate": 24000,
"normalize_audio": true,
"target_dB_FS": -25,
"eps": 1e-06
},
"language_model_pretrained_name": "Qwen/Qwen2.5-7B"
} |