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README.md

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+
+---
+license: cc-by-nc-4.0
+tags:
+- mms
+- vits
+pipeline_tag: text-to-speech
+---
+
+# Massively Multilingual Speech (MMS) : Text-to-Speech Models
+
+This repository contains the **Ayta, Abellen (abp)** language text-to-speech (TTS) model checkpoint.
+
+This model is part of Facebook's [Massively Multilingual Speech](https://arxiv.org/abs/2305.13516) project, aiming to
+provide speech technology across a diverse range of languages. You can find more details about the supported languages
+and their ISO 639-3 codes in the [MMS Language Coverage
+Overview](https://dl.fbaipublicfiles.com/mms/misc/language_coverage_mms.html).
+
+## Usage
+
+Using this checkpoint from Hugging Face Transformers:
+
+```python
+from transformers import VitsModel, VitsMmsTokenizer
+import torch
+
+model = VitsModel.from_pretrained("Matthijs/mms-tts-abp")
+tokenizer = VitsMmsTokenizer.from_pretrained("Matthijs/mms-tts-abp")
+
+text = "some example text in the Ayta, Abellen language"
+inputs = tokenizer(text, return_tensors="pt")
+
+with torch.no_grad():
+    output = model(**inputs)
+
+from IPython.display import Audio
+Audio(output.audio[0], rate=16000)
+```
+
+Note: For certain checkpoints, the input text must be converted to the Latin alphabet first using the
+[uroman](https://github.com/isi-nlp/uroman) tool.
+
+## Model credits
+
+This model was developed by Vineel Pratap et al. and is licensed as **CC-BY-NC 4.0**
+
+    @article{pratap2023mms,
+        title={Scaling Speech Technology to 1,000+ Languages},
+        author={Vineel Pratap and Andros Tjandra and Bowen Shi and Paden Tomasello and Arun Babu and Sayani Kundu and Ali Elkahky and Zhaoheng Ni and Apoorv Vyas and Maryam Fazel-Zarandi and Alexei Baevski and Yossi Adi and Xiaohui Zhang and Wei-Ning Hsu and Alexis Conneau and Michael Auli},
+        journal={arXiv},
+        year={2023}
+    }