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:
- 9948c75f9c14d166652dee38424d77d62b7090c7c52df3c10451310d52f9a556
- Size of remote file:
- 17.2 MB
- SHA256:
- 1a222563314bf6ffe3471622bff017ff5bb0630f2924faf44216195ebfef2af3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.