Instructions to use facebook/mms-tts-eng with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mms-tts-eng with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="facebook/mms-tts-eng")# Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("facebook/mms-tts-eng") model = AutoModelForTextToWaveform.from_pretrained("facebook/mms-tts-eng") - Notebooks
- Google Colab
- Kaggle
Commit ·
a507bf2
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Parent(s): 37c07f0
Upload model
Browse files- config.json +1 -0
config.json
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"speaker_embedding_size": 0,
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"speaking_rate": 1.0,
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"spectrogram_bins": 513,
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"sampling_rate": 16000,
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"speaker_embedding_size": 0,
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"speaking_rate": 1.0,
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"spectrogram_bins": 513,
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