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 run_fast_speech_2.py from Nithu/text-to-speech: direct link, hf CLI and curl.
- Browser
- Download file 306 Bytes
-
https://huggingface.co/Nithu/text-to-speech/resolve/main/run_fast_speech_2.py
- Command line
-
hf download hf://Nithu/text-to-speech/run_fast_speech_2.py
-
curl -L -o run_fast_speech_2.py https://huggingface.co/Nithu/text-to-speech/resolve/main/run_fast_speech_2.py
306 Bytes
| #!/usr/bin/env python3 | |
| from fairseq.checkpoint_utils import load_model_ensemble_and_task | |
| # model = load_model_ensemble_and_task(["./pytorch_model.pt"], arg_overrides={"config_yaml": "./config.yaml", "data": "./"}) | |
| model = load_model_ensemble_and_task(["./pytorch_model.pt"], arg_overrides={"data": "./"}) | |