Instructions to use TheStageAI/pocket-tts-100m-el with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Pocket-TTS
How to use TheStageAI/pocket-tts-100m-el with Pocket-TTS:
from pocket_tts import TTSModel import scipy.io.wavfile tts_model = TTSModel.load_model("TheStageAI/pocket-tts-100m-el") 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
pocket-tts-100m-el โ TheStage Apple SDK engines
Core ML / ANE engines of the Greek 100M-parameter Pocket TTS fine-tune
myned-ai/pocket-tts-greek by myned-ai (CC-BY-4.0; ~2,400 h of Greek speech, eight curated voices (two Cypriot)),
built on kyutai/pocket-tts, for the TheStage Apple SDK
(model_type: pocket-tts, bundle language el).
subscription/macos_ios/engines.zip (174 MB) โ flow LM fp16 with 6-bit g8 palettized transformer layers
(6 layers, d=1024, LSD flow head, ANE), Mimi decoder fp32 (CPU), voices: athina (default, the author's reference voice), eleni, giorgos, katerina, kostas, nikos, sophia, spyros, plus the English references azelma, alba, charles, cosette, javert, marius. QLPA-encrypted engines.
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