Instructions to use suleiman2003/mms-hausa-multispeaker-template with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use suleiman2003/mms-hausa-multispeaker-template with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="suleiman2003/mms-hausa-multispeaker-template")# Load model directly from transformers import MultiSpeakerVITS model = MultiSpeakerVITS.from_pretrained("suleiman2003/mms-hausa-multispeaker-template", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dc6f86e6f97e1787baf0b7e10127fbfe393d784b3e4cd0562e80a8ebb3221ce2
- Size of remote file:
- 145 MB
- SHA256:
- 6e5af27915bc9e96cee3a88782fc67baf56ce0cf6686920b9f27ad74ec546229
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