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:
- ea2d6f942296b157c7ae0ed9f02e1019daeace89f291dcfaa57a8932a1a32988
- Size of remote file:
- 1.98 GB
- SHA256:
- 81c3891f7b2493eb48a9eb6f5be0df48d4f1a4bfd952d84e21683ca6d0bf7969
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