Instructions to use BHOSAI/SARA_TTS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BHOSAI/SARA_TTS with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="BHOSAI/SARA_TTS")# Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("BHOSAI/SARA_TTS") model = AutoModelForTextToWaveform.from_pretrained("BHOSAI/SARA_TTS") - Notebooks
- Google Colab
- Kaggle
Voice of SARA
Baku Higher Oil School Research and Development Center on AI introduce their new Text-to-Speech model in collaboration with PRODATA. Model is based on VITS architecture, referenced to Meta MMS on Azerbaijani.
(c) Image has been generated by using Microsoft AI Image Generator!
Meta MMS model has good performance in naturalness of the speech while it was not robust to the change in the input tokens. Intonation varied according to the input tokens.
Our team has built speech and text pairs from public sources and combined them with 2-3 sentences to create continuous speech in the input.
Thanks to Kavsar Huseynova, Elvin Mammadov, Qurban Quliyev and PRODATA for the the contributions to this project!
All rights are reserved!
Note: Team and collaborators are not responsible about the contents of the generated voices by different individuals!
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Model tree for BHOSAI/SARA_TTS
Base model
facebook/mms-tts