Instructions to use BHOSAI/SARA_TTS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BHOSAI/SARA_TTS with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="BHOSAI/SARA_TTS")# Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("BHOSAI/SARA_TTS") model = AutoModelForTextToWaveform.from_pretrained("BHOSAI/SARA_TTS", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f7847385e28a24bfc11dc26c97089dc25689d7fe94074fb5489b8f191d97a143
- Size of remote file:
- 145 MB
- SHA256:
- 1c5413e0ed51c5421d74b61b229535a879e4b35c72ef9cd0272fc83bb199404d
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