Text-to-Speech
Transformers
ONNX
teratts_onnx
feature-extraction
onnxruntime
russian
english
custom-code
custom_code
Instructions to use Disya/TeraTTSv2-Duplicate-for-testing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Disya/TeraTTSv2-Duplicate-for-testing with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="Disya/TeraTTSv2-Duplicate-for-testing", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Disya/TeraTTSv2-Duplicate-for-testing", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download __pycache__/modeling_teratts.cpython-312.pyc from Disya/TeraTTSv2-Duplicate-for-testing: direct link, hf CLI and curl.
- Browser
- Download file 5 kB
-
https://huggingface.co/Disya/TeraTTSv2-Duplicate-for-testing/resolve/main/__pycache__/modeling_teratts.cpython-312.pyc
- Command line
-
hf download hf://Disya/TeraTTSv2-Duplicate-for-testing/__pycache__/modeling_teratts.cpython-312.pyc
-
curl -L -o modeling_teratts.cpython-312.pyc https://huggingface.co/Disya/TeraTTSv2-Duplicate-for-testing/resolve/main/__pycache__/modeling_teratts.cpython-312.pyc
5 kB
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