Instructions to use Nithu/text-to-speech with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Fairseq
How to use Nithu/text-to-speech with Fairseq:
from fairseq.checkpoint_utils import load_model_ensemble_and_task_from_hf_hub models, cfg, task = load_model_ensemble_and_task_from_hf_hub( "Nithu/text-to-speech" ) - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.pt from Nithu/text-to-speech: direct link, hf CLI and curl.
- Browser
- Download file 495 MB
-
https://huggingface.co/Nithu/text-to-speech/resolve/6489817a15ebb8e792056a697e7883bfc5737130/pytorch_model.pt
- Command line
-
hf download hf://Nithu/text-to-speech@6489817a15ebb8e792056a697e7883bfc5737130/pytorch_model.pt
-
curl -L -o pytorch_model.pt https://huggingface.co/Nithu/text-to-speech/resolve/6489817a15ebb8e792056a697e7883bfc5737130/pytorch_model.pt
495 MB
- Xet hash:
- 36559fc8cf0602730bb14747e1c8415b182f7c11f416cb519d244b2079ffa19f
- Size of remote file:
- 495 MB
- SHA256:
- a48d454fe66939079d0ddb70f1c062ec669f521a7cfadc608968746e312986ab
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.