Instructions to use facebook/mms-tts-plw with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mms-tts-plw with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="facebook/mms-tts-plw")# Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("facebook/mms-tts-plw") model = AutoModelForTextToWaveform.from_pretrained("facebook/mms-tts-plw") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 29d59ee3268b6070fa7ebd4d58a2fd28c30de172ccb002033fcd069bf8e50b8c
- Size of remote file:
- 145 MB
- SHA256:
- 2acaa6bd24bf78ee7765306f24afc934f3a5b033cb7009fc3a9556021ee1158e
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