Instructions to use facebook/mms-tts-sag with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mms-tts-sag with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="facebook/mms-tts-sag")# Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("facebook/mms-tts-sag") model = AutoModelForTextToWaveform.from_pretrained("facebook/mms-tts-sag", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f6c29c02a15fb959797a8f8769cf91630090fab782f6aa1242b5984805bf02ed
- Size of remote file:
- 145 MB
- SHA256:
- d8fa29e1060e130798dd13cdc0309903332e08444c05d6c7a406be67232c5cc1
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