Instructions to use facebook/mms-tts-urd-script_latin with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mms-tts-urd-script_latin 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_latin")# Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("facebook/mms-tts-urd-script_latin") model = AutoModelForTextToWaveform.from_pretrained("facebook/mms-tts-urd-script_latin") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f30d09f046b1ab3a8f3f52a985bf157b5d6c9bb9b21597dccbb624add32b5af8
- Size of remote file:
- 145 MB
- SHA256:
- 2e3d8046161061a740f364807bc91036bfee854b6456439e4565becf37b9601d
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