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")# 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 tokenizer_config.json from facebook/mms-tts-nan: direct link, hf CLI and curl.
- Browser
- Download file 287 Bytes
-
https://huggingface.co/facebook/mms-tts-nan/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://facebook/mms-tts-nan/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/facebook/mms-tts-nan/resolve/main/tokenizer_config.json
287 Bytes
| { | |
| "add_blank": true, | |
| "clean_up_tokenization_spaces": true, | |
| "is_uroman": false, | |
| "language": "nan", | |
| "model_max_length": 1000000000000000019884624838656, | |
| "normalize": true, | |
| "pad_token": "|", | |
| "phonemize": false, | |
| "tokenizer_class": "VitsTokenizer", | |
| "unk_token": "<unk>" | |
| } | |