Instructions to use facebook/mms-tts-srn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mms-tts-srn with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="facebook/mms-tts-srn")# Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("facebook/mms-tts-srn") model = AutoModelForTextToWaveform.from_pretrained("facebook/mms-tts-srn", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0ab1950aa2906c44eaa90109bca047a3ec0de04a4d0c672b48e59f72df252092
- Size of remote file:
- 145 MB
- SHA256:
- 3c2c0101436a481bd3524723573f128cf5eebeaf334180e52ac1906205b09b88
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