Instructions to use bosonai/higgs-tts-2-3b-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bosonai/higgs-tts-2-3b-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="bosonai/higgs-tts-2-3b-base")# Load model directly from transformers import AutoProcessor, AutoModelForTextToWaveform processor = AutoProcessor.from_pretrained("bosonai/higgs-tts-2-3b-base") model = AutoModelForTextToWaveform.from_pretrained("bosonai/higgs-tts-2-3b-base") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- d8a368f294d1862bfabf29c837167cbb79bf7980cc38abbb291c043d3b478b08
- Size of remote file:
- 117 kB
- SHA256:
- f7c0177e38dd9c873acf8ac55c159ce65ba50970cbeba9663582da4698037447
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.