Instructions to use team-edt/enclave-tts with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Pocket-TTS
How to use team-edt/enclave-tts with Pocket-TTS:
from pocket_tts import TTSModel import scipy.io.wavfile tts_model = TTSModel.load_model("team-edt/enclave-tts") 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
Enclave TTS assets (pocket-tts, ONNX)
Voice-model assets used by the Enclave browser extension to synthesize speech locally, on-device. Hosted here only so the extension can fetch them once and cache them; nothing about how they're used is changed.
Attribution & license
These weights are Kyutai pocket-tts, licensed CC-BY-4.0. This repository redistributes them under the same license, with attribution to Kyutai.
Changes made to the original:
- Exported from the official safetensors weights to ONNX and int8-quantized, using KevinAHM/pocket-tts-onnx-export (export code: MIT).
- Only the
albavoice is included (from kyutai/tts-voices โalba-mackenna, CC-BY-4.0). The other voices from the upstream bundle โ some of which are CC-BY-NC โ are not redistributed here.
Acceptable use
Per Kyutai's model terms: use must comply with applicable law and must not involve voice impersonation/cloning without consent, misinformation, or other harmful use. Enclave uses a single fixed preset voice to read the assistant's own generated replies aloud โ no cloning.
Contents
bundle.json, tokenizer.model, bos_before_voice.npy,
text_conditioner_int8.onnx, flow_lm_main_int8.onnx, flow_lm_flow_int8.onnx,
mimi_decoder_int8.onnx, voices.bin (alba only).
Regenerate with node scripts/prepare-tts-assets.mjs in the Enclave repo.
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