Instructions to use kyutai/pocket-tts-without-voice-cloning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Pocket-TTS
How to use kyutai/pocket-tts-without-voice-cloning with Pocket-TTS:
from pocket_tts import TTSModel import scipy.io.wavfile tts_model = TTSModel.load_model("kyutai/pocket-tts-without-voice-cloning") 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
Add pipeline tag and library name to metadata
#1
by nielsr HF Staff - opened
Hi! I'm Niels from the Hugging Face community team.
I've opened this PR to improve the model card's discoverability. I've added the text-to-speech pipeline tag and the library_name: pocket-tts to the metadata. I've also included a link to the project page in the header. These changes help users find the model more easily and understand how to use it with the associated library.
The rest of the content remains unchanged as it already provides excellent documentation.
Thank you!
gabrielatkyutail changed pull request status to merged