Instructions to use espnet/fastspeech2_conformer_with_hifigan with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use espnet/fastspeech2_conformer_with_hifigan with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="espnet/fastspeech2_conformer_with_hifigan")# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForTextToWaveform model = AutoModelForTextToWaveform.from_pretrained("espnet/fastspeech2_conformer_with_hifigan", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from espnet/fastspeech2_conformer_with_hifigan: direct link, hf CLI and curl.
- Browser
- Download file 337 MB
-
https://huggingface.co/espnet/fastspeech2_conformer_with_hifigan/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://espnet/fastspeech2_conformer_with_hifigan/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/espnet/fastspeech2_conformer_with_hifigan/resolve/main/pytorch_model.bin
337 MB
- Xet hash:
- 39bebf052e71b0e9b791f87c16c9095775199115494c7a96514b8bdcc510a6b8
- Size of remote file:
- 337 MB
- SHA256:
- 4c9d7bd71f026b7d60d5e7ec5e92edb5fdabe68ff88dc0cea696c2f2dd7fee0f
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