Instructions to use facebook/mms-tts-nan with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mms-tts-nan with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="facebook/mms-tts-nan")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("facebook/mms-tts-nan") model = AutoModelForTextToWaveform.from_pretrained("facebook/mms-tts-nan", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download vocab.json from facebook/mms-tts-nan: direct link, hf CLI and curl.
- Browser
- Download file 549 Bytes
-
https://huggingface.co/facebook/mms-tts-nan/resolve/b15e97d3b4f3d33a427d375d0fda8d51494b062f/vocab.json
- Command line
-
hf download hf://facebook/mms-tts-nan@b15e97d3b4f3d33a427d375d0fda8d51494b062f/vocab.json
-
curl -L -o vocab.json https://huggingface.co/facebook/mms-tts-nan/resolve/b15e97d3b4f3d33a427d375d0fda8d51494b062f/vocab.json
549 Bytes
| { | |
| " ": 47, | |
| "'": 45, | |
| "-": 2, | |
| "a": 8, | |
| "b": 28, | |
| "c": 9, | |
| "e": 15, | |
| "g": 7, | |
| "h": 1, | |
| "i": 3, | |
| "j": 38, | |
| "k": 6, | |
| "l": 11, | |
| "m": 26, | |
| "n": 4, | |
| "o": 12, | |
| "p": 19, | |
| "s": 10, | |
| "t": 5, | |
| "u": 24, | |
| "|": 0, | |
| "à": 29, | |
| "á": 23, | |
| "â": 16, | |
| "è": 30, | |
| "é": 41, | |
| "ê": 13, | |
| "ì": 32, | |
| "í": 21, | |
| "î": 36, | |
| "ò": 31, | |
| "ó": 17, | |
| "ô": 33, | |
| "ù": 35, | |
| "ú": 34, | |
| "û": 39, | |
| "ā": 22, | |
| "ē": 37, | |
| "ī": 25, | |
| "ń": 44, | |
| "ō": 18, | |
| "ū": 20, | |
| "ǹ": 42, | |
| "̂": 43, | |
| "̄": 40, | |
| "̍": 14, | |
| "͘": 27, | |
| "ḿ": 46 | |
| } | |