Automatic Speech Recognition
Transformers
Safetensors
Twi
vits
text-to-audio
audio
speech
african-languages
multilingual
simba
low-resource
speech-recognition
asr
Instructions to use UBC-NLP/Simba-TTS-twi-akuapem with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UBC-NLP/Simba-TTS-twi-akuapem with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="UBC-NLP/Simba-TTS-twi-akuapem")# Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("UBC-NLP/Simba-TTS-twi-akuapem") model = AutoModelForTextToWaveform.from_pretrained("UBC-NLP/Simba-TTS-twi-akuapem") - Notebooks
- Google Colab
- Kaggle
Welcome to the community
The community tab is the place to discuss and collaborate with the HF community!