Text-to-Speech
Transformers
Safetensors
Hausa
vits
text-to-audio
tts
mms
nigerian-languages
low-resource
waxal
soro-tts
hausa
Eval Results (legacy)
Instructions to use Shinzmann/soro-tts-hau with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shinzmann/soro-tts-hau with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="Shinzmann/soro-tts-hau")# Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("Shinzmann/soro-tts-hau") model = AutoModelForTextToWaveform.from_pretrained("Shinzmann/soro-tts-hau") - Notebooks
- Google Colab
- Kaggle
Welcome to the community
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