Instructions to use facebook/mms-tts-bmr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mms-tts-bmr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="facebook/mms-tts-bmr")# Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("facebook/mms-tts-bmr") model = AutoModelForTextToWaveform.from_pretrained("facebook/mms-tts-bmr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d51b1307d267af825c41b1eead31b0a7e3ab9562f2c962baa82bae6edbd90e5c
- Size of remote file:
- 145 MB
- SHA256:
- f33135564d6afe3290faf7d6d5fea7c303bcdd51b31b1df7a2f7c6ff3271ab02
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