Text-to-Speech
Transformers
ONNX
speech-synthesis
multilingual
indic
orpheus
quantized
low-latency
zero-shot
emotions
discrete-audio-tokens
onnxruntime-genai
Instructions to use Prince-1/svara-tts-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Prince-1/svara-tts-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="Prince-1/svara-tts-v1")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Prince-1/svara-tts-v1", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 01275e9772d729be807c6665b2618ef943a46103445e3e2c5af06b5d1686671d
- Size of remote file:
- 6.64 GB
- SHA256:
- 5b2d688b7b60155f6b39db247b67e6c9f8e7155350333f997b7b31aa6a2af771
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.