Instructions to use rsxdalv/VibeVoice-1.5B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rsxdalv/VibeVoice-1.5B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="rsxdalv/VibeVoice-1.5B")# Load model directly from transformers import AutoModelForSeq2SeqLM model = AutoModelForSeq2SeqLM.from_pretrained("rsxdalv/VibeVoice-1.5B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1f6fc4792626894f29896dff6ebc6ce8e81a07110b9376ea8e82b94cd57f798b
- Size of remote file:
- 1.98 GB
- SHA256:
- c5f0a61ddeaeb028e3af540ba4dee7933ad30f9f30b6e1320dd9c875a2daa033
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