Instructions to use facebook/mms-tts-kan with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mms-tts-kan with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="facebook/mms-tts-kan")# Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("facebook/mms-tts-kan") model = AutoModelForTextToWaveform.from_pretrained("facebook/mms-tts-kan", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 853957af68473d50f2b8c6d6f1d85b94248269c87bd1de43d78fc903386033c5
- Size of remote file:
- 145 MB
- SHA256:
- 0263ab060d7bce84453d19fbe550eb73e2f26a7e1fc683cdcf9f34681f4fe999
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