Instructions to use itzune/pocket-tts-basque with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Pocket-TTS
How to use itzune/pocket-tts-basque with Pocket-TTS:
from pocket_tts import TTSModel import scipy.io.wavfile tts_model = TTSModel.load_model("itzune/pocket-tts-basque") 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 tokenizer.model from itzune/pocket-tts-basque: direct link, hf CLI and curl.
- Browser
- Download file 60.6 kB
-
https://huggingface.co/itzune/pocket-tts-basque/resolve/main/tokenizer.model
- Command line
-
hf download hf://itzune/pocket-tts-basque/tokenizer.model
-
curl -L -o tokenizer.model https://huggingface.co/itzune/pocket-tts-basque/resolve/main/tokenizer.model
60.6 kB
- Xet hash:
- 76d8fdf8ed63c5bc329dbc585da7afec95e5e5c2ed061b14bf1365296703e629
- Size of remote file:
- 60.6 kB
- SHA256:
- b1087073d2b9fc865b81655f0dc0acfa55bc25b57f0d49f52f4e2ad0dcb0a967
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