Instructions to use facebook/mms-tts-khm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mms-tts-khm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="facebook/mms-tts-khm")# Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("facebook/mms-tts-khm") model = AutoModelForTextToWaveform.from_pretrained("facebook/mms-tts-khm") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4c7bd936af88057a4edca2452b6c8271be91432cc964eb2cdabe03ba7ed50439
- Size of remote file:
- 145 MB
- SHA256:
- 1bf459a25f34456652e3170644f5a84ef7fb1972ed0a238733f148373612ba25
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