Yurii Paniv commited on
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ca51157
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Update README.md

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  1. README.md +4 -4
README.md CHANGED
@@ -18,13 +18,13 @@ Link to source code and models -> [https://github.com/robinhad/ukrainian-tts](ht
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  Telegram bot -> [https://t.me/uk_tts_bot](https://t.me/uk_tts_bot)
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  Code is licensed under `MIT License`, models are under `GNU GPL v3 License`.
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- # Support
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- If you like my work, please support -> [https://send.monobank.ua/jar/48iHq4xAXm](https://send.monobank.ua/jar/48iHq4xAXm)
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  For collaboration and question please contact me here:
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  [Telegram https://t.me/robinhad](https://t.me/robinhad)
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  [Twitter https://twitter.com/robinhad](https://twitter.com/robinhad)
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  You're welcome to join UA Speech Recognition and Synthesis community: [Telegram https://t.me/speech_recognition_uk](https://t.me/speech_recognition_uk)
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- # Examples
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  `Mykyta (male)`:
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@@ -49,7 +49,7 @@ https://user-images.githubusercontent.com/5759207/190852259-c6746172-05c4-4918-8
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  https://user-images.githubusercontent.com/5759207/190852270-7aed2db9-dc08-4a9f-8775-07b745657ca1.mp4
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- # How to use:
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  Caution: this won't use normalizer and autostress like a web demo.
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  1. `pip install -r requirements.txt`.
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  2. Download `model.pth` and `speakers.pth` from "Releases" tab.
 
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  Telegram bot -> [https://t.me/uk_tts_bot](https://t.me/uk_tts_bot)
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  Code is licensed under `MIT License`, models are under `GNU GPL v3 License`.
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+ # Support ❤️
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+ If you like my work, please support ❤️ -> [https://send.monobank.ua/jar/48iHq4xAXm](https://send.monobank.ua/jar/48iHq4xAXm)
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  For collaboration and question please contact me here:
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  [Telegram https://t.me/robinhad](https://t.me/robinhad)
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  [Twitter https://twitter.com/robinhad](https://twitter.com/robinhad)
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  You're welcome to join UA Speech Recognition and Synthesis community: [Telegram https://t.me/speech_recognition_uk](https://t.me/speech_recognition_uk)
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+ # Examples 🤖
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  `Mykyta (male)`:
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  https://user-images.githubusercontent.com/5759207/190852270-7aed2db9-dc08-4a9f-8775-07b745657ca1.mp4
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+ # How to use: 📢
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  Caution: this won't use normalizer and autostress like a web demo.
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  1. `pip install -r requirements.txt`.
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  2. Download `model.pth` and `speakers.pth` from "Releases" tab.