Instructions to use facebook/mms-tts-urd-script_devanagari with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mms-tts-urd-script_devanagari with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="facebook/mms-tts-urd-script_devanagari")# Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("facebook/mms-tts-urd-script_devanagari") model = AutoModelForTextToWaveform.from_pretrained("facebook/mms-tts-urd-script_devanagari", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bdd90d0f969e5326174cab789810d450ca4981e6dd5e158ab98a81179e016920
- Size of remote file:
- 145 MB
- SHA256:
- 96da2e38fb22ae09a0cbaee460f64e3d3e16deeb713f29b1b8ed9caf9552bd94
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