Instructions to use facebook/mms-tts-ded with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mms-tts-ded with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="facebook/mms-tts-ded")# Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("facebook/mms-tts-ded") model = AutoModelForTextToWaveform.from_pretrained("facebook/mms-tts-ded", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 287 Bytes
2c6ef9d | 1 2 3 4 5 6 7 8 9 10 11 12 13 | {
"add_blank": true,
"clean_up_tokenization_spaces": true,
"is_uroman": false,
"language": "ded",
"model_max_length": 1000000000000000019884624838656,
"normalize": true,
"pad_token": "k",
"phonemize": false,
"tokenizer_class": "VitsTokenizer",
"unk_token": "<unk>"
}
|