Instructions to use facebook/mms-tts-hlb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mms-tts-hlb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="facebook/mms-tts-hlb")# Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("facebook/mms-tts-hlb") model = AutoModelForTextToWaveform.from_pretrained("facebook/mms-tts-hlb", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9a537ce2bb6db5785052bf6c256dd25936c208e684f8286a7733f0c9c11c7c61
- Size of remote file:
- 145 MB
- SHA256:
- b50659244d422ec48e10d6400d2dc53805aef6d0482607e28f2ccd77c0ad3299
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