Text-to-Speech
Transformers
ONNX
teratts_onnx
feature-extraction
onnxruntime
russian
english
custom-code
custom_code
Instructions to use TeraSpace/TeraTTSv2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TeraSpace/TeraTTSv2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="TeraSpace/TeraTTSv2", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("TeraSpace/TeraTTSv2", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dc5b54bdf0f65de6a76f2cdb1528a4f41b466005b0bf06519fad992567a98f8b
- Size of remote file:
- 27.9 MB
- SHA256:
- d59b7911fe9e465988f26bedbf7c34ef9b2c5588d9b0da5f86d41340a3324a12
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