Instructions to use facebook/mms-tts-urd-script_arabic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mms-tts-urd-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-urd-script_arabic")# Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("facebook/mms-tts-urd-script_arabic") model = AutoModelForTextToWaveform.from_pretrained("facebook/mms-tts-urd-script_arabic", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c07c4ad4f48f666ca57e80c740047a50c5544e33905805242f3b79319b9e67b7
- Size of remote file:
- 145 MB
- SHA256:
- e7da672f856f8cc23d30075f925ce42ed8015cbdbaccbdc2e1bc137ee43af71a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.