Instructions to use wite-tech/pocket-tts-turkish with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Pocket-TTS
How to use wite-tech/pocket-tts-turkish with Pocket-TTS:
from pocket_tts import TTSModel import scipy.io.wavfile tts_model = TTSModel.load_model("wite-tech/pocket-tts-turkish") voice_state = tts_model.get_state_for_audio_prompt( "hf://kyutai/tts-voices/alba-mackenna/casual.wav" ) audio = tts_model.generate_audio(voice_state, "Hello world, this is a test.") # Audio is a 1D torch tensor containing PCM data. scipy.io.wavfile.write("output.wav", tts_model.sample_rate, audio.numpy()) - Notebooks
- Google Colab
- Kaggle
Download figures/fig2_speed_vs_wer.png from wite-tech/pocket-tts-turkish: direct link, hf CLI and curl.
- Browser
- Download file 189 kB
-
https://huggingface.co/wite-tech/pocket-tts-turkish/resolve/main/figures/fig2_speed_vs_wer.png
- Command line
-
hf download hf://wite-tech/pocket-tts-turkish/figures/fig2_speed_vs_wer.png
-
curl -L -o fig2_speed_vs_wer.png https://huggingface.co/wite-tech/pocket-tts-turkish/resolve/main/figures/fig2_speed_vs_wer.png
189 kB

- Xet hash:
- cb3669f1367eeab8c78b7534f6b0d6d5cc0e9bd85b68ce05a92952cf6266e6e9
- Size of remote file:
- 189 kB
- SHA256:
- 4b31147c3dad80227d4f9e92f8868a25bfd4f4818fc51b13e8e589902c5743a8
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