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 pytorch_model.bin from YeQing/speecht5_tts_commonvioce_zh: direct link, hf CLI and curl.
- Browser
- Download file 585 MB
-
https://huggingface.co/YeQing/speecht5_tts_commonvioce_zh/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://YeQing/speecht5_tts_commonvioce_zh/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/YeQing/speecht5_tts_commonvioce_zh/resolve/main/pytorch_model.bin
585 MB
- Xet hash:
- fe2346e1e3df0db9658dafd9c7d7d31b7af45714176b168ac39d8090573cdde4
- Size of remote file:
- 585 MB
- SHA256:
- c93bbba434a9e43c0b0ef6381ff7a6e3153e989c1ae5ccd38c59448866251839
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.