Instructions to use ks2303/tts-transformer-ljspeech with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ks2303/tts-transformer-ljspeech with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="ks2303/tts-transformer-ljspeech")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ks2303/tts-transformer-ljspeech", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update hparams.yaml
Browse files- hparams.yaml +0 -2
hparams.yaml
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############################################################################
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# Model: TransformerTTS
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# Tokens: Phonemes (English)
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# losses: Transducer
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# Training: LJSpeech
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# Author: Kasturi Saha
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# ############################################################################
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############################################################################
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# Model: TransformerTTS
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# Training: LJSpeech
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# Author: Kasturi Saha
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# ############################################################################
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