Instructions to use facebook/mms-tts-hat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mms-tts-hat with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="facebook/mms-tts-hat")# Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("facebook/mms-tts-hat") model = AutoModelForTextToWaveform.from_pretrained("facebook/mms-tts-hat", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4481933aa0ebfc5cc4061d4bb8e2ba74573cd9a0c20d63c331208330ef823115
- Size of remote file:
- 145 MB
- SHA256:
- 2efdf8c7c627ebc78093547b6ef660568f46afb77f94758117e93d273a090d19
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