Instructions to use jaketae/fastspeech2-ljspeech with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jaketae/fastspeech2-ljspeech with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jaketae/fastspeech2-ljspeech", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from jaketae/fastspeech2-ljspeech: direct link, hf CLI and curl.
- Browser
- Download file 166 MB
-
https://huggingface.co/jaketae/fastspeech2-ljspeech/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://jaketae/fastspeech2-ljspeech/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/jaketae/fastspeech2-ljspeech/resolve/main/pytorch_model.bin
166 MB
- Xet hash:
- f13a85a55981b5166344d62eed3f46f91c787a627b70f5161e9a7ee27e983434
- Size of remote file:
- 166 MB
- SHA256:
- 513573603ef1d07211bef95c231edd57cf417915992b45c451c2eb1a442aa6ff
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