Text-to-Speech
Transformers
Safetensors
Arabic
moss_tts_local
feature-extraction
voice-cloning
custom_code
sglang-omni
moss-tts
moss-tts-local
lora
saudi-arabic
Instructions to use Rabe3/saudi-tts-4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rabe3/saudi-tts-4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="Rabe3/saudi-tts-4", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Rabe3/saudi-tts-4", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 45c8805c0411777f0ac2eb2d687f722505d7895fbad0bd25ad7c6b10532d4747
- Size of remote file:
- 11.4 MB
- SHA256:
- e121b329d48e63a62bad58e1b37d2f916c563dd997c7e25d63f88cdd2f6bbbe5
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