Instructions to use facebook/mms-tts-tgl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mms-tts-tgl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="facebook/mms-tts-tgl")# Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("facebook/mms-tts-tgl") model = AutoModelForTextToWaveform.from_pretrained("facebook/mms-tts-tgl", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 07bb8cc475257cdfd8bd9ffdd02a6dde9303bada86c715cc6e0b2eaec0e6dc9c
- Size of remote file:
- 145 MB
- SHA256:
- 7350fce1d1984f5254f1b8c9f535e0de6535510e93669f8c941ecbc8e046b7bd
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