Instructions to use rs545837/speecht5_jenny_500 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rs545837/speecht5_jenny_500 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="rs545837/speecht5_jenny_500")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("rs545837/speecht5_jenny_500") model = AutoModelForTextToSpectrogram.from_pretrained("rs545837/speecht5_jenny_500", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from rs545837/speecht5_jenny_500: direct link, hf CLI and curl.
- Browser
- Download file 5.24 kB
-
https://huggingface.co/rs545837/speecht5_jenny_500/resolve/main/training_args.bin
- Command line
-
hf download hf://rs545837/speecht5_jenny_500/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/rs545837/speecht5_jenny_500/resolve/main/training_args.bin
5.24 kB
- Xet hash:
- dfdb599de218fab04f9f0599d42d5f02a14a2e2d7589dded330e749f30ae580f
- Size of remote file:
- 5.24 kB
- SHA256:
- 70861960ba61c4da8aa029cd5298e9d2dda64abbbbd4ca49e6d32fe2e75b76bb
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