Instructions to use vibevoice/VibeVoice-7B-hf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vibevoice/VibeVoice-7B-hf with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="vibevoice/VibeVoice-7B-hf")# Load model directly from transformers import AutoProcessor, AutoModelForTextToWaveform processor = AutoProcessor.from_pretrained("vibevoice/VibeVoice-7B-hf") model = AutoModelForTextToWaveform.from_pretrained("vibevoice/VibeVoice-7B-hf", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d3f835122bddb470f53048ff36f1a5116791b8f3a003f9d17b3b03b0b81cc5fe
- Size of remote file:
- 11.4 MB
- SHA256:
- 3fd169731d2cbde95e10bf356d66d5997fd885dd8dbb6fb4684da3f23b2585d8
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