Instructions to use facebook/mms-tts-aca with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mms-tts-aca with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="facebook/mms-tts-aca")# Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("facebook/mms-tts-aca") model = AutoModelForTextToWaveform.from_pretrained("facebook/mms-tts-aca") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b2f8ee10abcf5fbdd1fb2a5dd3742308ea0f6b9b7f12d0dc311e3f70e1af3d1c
- Size of remote file:
- 145 MB
- SHA256:
- 24fe0d7e98172d49a379d376fc5c1ba3c35ab97a58aaf452bd4db04864dd98b4
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