Instructions to use fav-kky/SpeechT5-base-cs-tts with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fav-kky/SpeechT5-base-cs-tts with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="fav-kky/SpeechT5-base-cs-tts")# Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("fav-kky/SpeechT5-base-cs-tts") model = AutoModelForTextToSpectrogram.from_pretrained("fav-kky/SpeechT5-base-cs-tts") - Notebooks
- Google Colab
- Kaggle
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This is a TTS variant of the SpeechT5 model,
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i.e., the input modality is text (processed via the text pre-net),
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and the output modality is speech (processed via the speech post-net).
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The model has the same format as the [
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In order to use this model for text-to-speech, it must be [fine-tuned](https://huggingface.co/learn/audio-course/chapter6/fine-tuning) on labeled TTS data.
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The usage is the same as for the [
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## Related works
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This is a TTS variant of the SpeechT5 model,
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i.e., the input modality is text (processed via the text pre-net),
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and the output modality is speech (processed via the speech post-net).
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The model has the same format as the [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) compatible with the [SpeechT5ForTextToSpeech class](https://huggingface.co/docs/transformers/model_doc/speecht5#transformers.SpeechT5ForTextToSpeech).
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In order to use this model for text-to-speech, it must be [fine-tuned](https://huggingface.co/learn/audio-course/chapter6/fine-tuning) on labeled TTS data.
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The usage is the same as for the [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts)
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## Related works
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