Instructions to use Foxasdf/ArabicTextToSpeech with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Foxasdf/ArabicTextToSpeech with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Foxasdf/ArabicTextToSpeech")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Foxasdf/ArabicTextToSpeech") model = AutoModelForCTC.from_pretrained("Foxasdf/ArabicTextToSpeech", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d0eea67f2b621e7bb5048c8b2cf7a98f784564bed67c60f3d36d383a1d492406
- Size of remote file:
- 3.96 kB
- SHA256:
- bb19db5702a3eb54a28605e0df12623fa3c46d1e64724cb74c91954950f7fd20
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