Instructions to use facebook/mms-tts-eng with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mms-tts-eng with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="facebook/mms-tts-eng")# Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("facebook/mms-tts-eng") model = AutoModelForTextToWaveform.from_pretrained("facebook/mms-tts-eng") - Notebooks
- Google Colab
- Kaggle
What kind of dataset was used?
#8
by f0rGoTTen000 - opened
What kind of dataset was used to build this model?
The dataset comprises of a single speaker narrating the New Testament. See section 7.2 of the paper for details: https://huggingface.co/papers/2305.13516
"train.txt" and "dev.txt" file
H:/MMS/Dataset/0001.wav|0|Line one is my favoryte.
audio file
wav - mono - 16000Hz - PCM - Little / Signed
These are the texts in my training script