Instructions to use theabbie/AbbieSpeak with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Pocket-TTS
How to use theabbie/AbbieSpeak with Pocket-TTS:
from pocket_tts import TTSModel import scipy.io.wavfile tts_model = TTSModel.load_model("theabbie/AbbieSpeak") 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
AbbieSpeak
Saved voice state for Kyutai Pocket TTS, made with pocket-tts export-voice. Nothing is trained: the file is loaded and only the generation step runs.
pocket-tts generate --voice hf://theabbie/AbbieSpeak/abbie.safetensors --text "Hello there."
Or with no setup besides uv (add HF_TOKEN while the repo is private):
hf download theabbie/AbbieSpeak speak.py --local-dir .
uv run speak.py "The quick brown fox jumps over the lazy dog." out.wav
Generation needs only the open kyutai/pocket-tts-without-voice-cloning weights; no gated access is required.
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