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:
- d4af7b1bd158ef2c7a22122fd57bb17f04a15cd10acdef14dfe4daa38832e050
- Size of remote file:
- 1.45 GB
- SHA256:
- cb6e7e5e86b4a41fffbe1f3aaf445d0d50b5e21ed47574101b777f77d75fa196
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.