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")# 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
Update README.md
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README.md
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torch.manual_seed(seed)
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np.random.seed(seed)
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# create conversation with an audio for the first time a speaker appears to clone that particular voice
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conversations = [
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{"role": "0", "content": [
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torch.manual_seed(seed)
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np.random.seed(seed)
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conversations = [
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{"role": "0", "content": [
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