Instructions to use facebook/mms-tts-uig-script_arabic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mms-tts-uig-script_arabic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="facebook/mms-tts-uig-script_arabic")# Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("facebook/mms-tts-uig-script_arabic") model = AutoModelForTextToWaveform.from_pretrained("facebook/mms-tts-uig-script_arabic") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d59570580902b02662ba86565ad127ec3c2e99465e8375ce5253d4e0429f17c9
- Size of remote file:
- 145 MB
- SHA256:
- a714ce583fa4bec2966ee0002aba84931b260f2fd7c49dd4466752b23abfd010
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