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amphion/vits_hifitts
vits_hifitts is a machine learning model from amphion. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
We provide the pre-trained checkpoint of VITS, trained on Hi-fi TTS, which consists of a total of 291.6 hours audio contributed by 10 speakers, on an average of 17 hours per speaker. To utilize the pre-trained model,…
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Updated Feb 23, 2024
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From the Hugging Face model README
We provide the pre-trained checkpoint of VITS, trained on Hi-fi TTS, which consists of a total of 291.6 hours audio contributed by 10 speakers, on an average of 17 hours per speaker. To utilize the pre-trained model, run the following commands:
git lfs install
git clone https://huggingface.co/amphion/vits_hifitts
git clone https://github.com/open-mmlab/Amphion.git
Use the soft link to specify the downloaded checkpoint in the first step:
cd Amphion
mkdir -p ckpts/tts
ln -s ../../../vits_hifitts ckpts/tts/
You can follow the inference part of this recipe to generate speech from text. For example, if you want to synthesize a clip of speech with the text of "This is a clip of generated speech with the given text from a TTS model.", just, run:
sh egs/tts/VITS/run.sh --stage 3 --gpu "0" \
--config ckpts/tts/vits_hifitts/args.json \
--infer_expt_dir ckpts/tts/vits_hifitts/ \
--infer_output_dir ckpts/tts/vits_hifitts/result \
--infer_mode "single" \
--infer_text "This is a clip of generated speech with the given text from a TTS model." \
--infer_speaker_name "hifitts_92"
Note: The supported infer_speaker_name values can be seen here.