Instructions to use YeQing/speecht5_tts_commonvioce_zh with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YeQing/speecht5_tts_commonvioce_zh with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="YeQing/speecht5_tts_commonvioce_zh")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("YeQing/speecht5_tts_commonvioce_zh") model = AutoModelForTextToSpectrogram.from_pretrained("YeQing/speecht5_tts_commonvioce_zh", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from YeQing/speecht5_tts_commonvioce_zh: direct link, hf CLI and curl.
- Browser
- Download file 4.09 kB
-
https://huggingface.co/YeQing/speecht5_tts_commonvioce_zh/resolve/main/training_args.bin
- Command line
-
hf download hf://YeQing/speecht5_tts_commonvioce_zh/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/YeQing/speecht5_tts_commonvioce_zh/resolve/main/training_args.bin
4.09 kB
- Xet hash:
- 1e5cb185bf6798381ebb080bfcbef17ead66eafcce1ddb75421c796cf7a95904
- Size of remote file:
- 4.09 kB
- SHA256:
- a94dadb13e4467e4ddf8316010c594f55c5c501072feb9995e50fa1d328f0dea
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.