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
File size: 569 Bytes
1f90181 e370e93 1f90181 f2fe7cd e370e93 1f90181 f2fe7cd 1f90181 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | {
"architectures": ["TeraTTSModel"],
"automatic_russian_stress": true,
"auto_map": {
"AutoConfig": "configuration_teratts.TeraTTSConfig",
"AutoModel": "modeling_teratts.TeraTTSModel"
},
"default_diffusion_model": "distilled",
"default_voice": "ru_f1",
"cross_language_prompt_note": "For an English reference voice speaking Russian, try duration_scale below 1.0.",
"model_type": "teratts_onnx",
"sample_rate": 44100,
"voices": ["eng_f3", "eng_f4_whisper", "eng_f5", "eng_m2_whisper", "eng_m3", "eng_m4", "ru_f1", "ru_f2", "ru_m1", "ru_m5"]
}
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