---
license: cc-by-nc-sa-4.0
datasets:
- openslr
- mozilla-foundation/common_voice_13_0
- Lagos-NWU_Yoruba_Speech_Corpus
language:
- yo
library_name: transformers
pipeline_tag: text-to-speech
---

```python 
# Load model directly
from transformers import SpeechT5Processor, SpeechT5ForTextToSpeech, SpeechT5HifiGan
from huggingface_hub import hf_hub_download
import torch

processor = SpeechT5Processor.from_pretrained("imhotepai/yoruba-tts")
model = SpeechT5ForTextToSpeech.from_pretrained("imhotepai/yoruba-tts")

dir_= hf_hub_download(repo_id="imhotepai/yoruba-tts", filename="speaker_embeddings.pt")
speaker_embeddings= torch.load(dir_)

text='Báwó ni'.lower()
inputs = processor(text=text, return_tensors="pt")

vocoder = SpeechT5HifiGan.from_pretrained("microsoft/speecht5_hifigan")
speech = model.generate_speech(inputs["input_ids"], speaker_embeddings, vocoder=vocoder)

# Audio in notebook
from IPython.display import Audio

Audio(speech.numpy(), rate=16000)
```