Instructions to use inklight-app/pocket-tts-q8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Pocket-TTS
How to use inklight-app/pocket-tts-q8 with Pocket-TTS:
from pocket_tts import TTSModel import scipy.io.wavfile tts_model = TTSModel.load_model("inklight-app/pocket-tts-q8") 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, Q8_0
Kyutai's Pocket TTS converted for Inklight, an iPhone app that reads books aloud on the device, and for PocketVoice Reader, a Firefox extension that reads web pages aloud. The FlowLM transformer reads all its weights once for every frame it generates, which makes it memory-bound on a phone; with its linear layers in Q8_0 it reads a quarter as much and renders about 30 % faster, and the file is little more than half the size of the original.
Files
One model.q8.gguf per language, about 129 MB each: english_2026-04, german, french, spanish and portuguese, each the model of the same name from kyutai/pocket-tts-without-voice-cloning (German, French, Spanish and Portuguese as of Kyutai's commit 1e08e6a of 2026-10-01, the versions pocket-tts 4.0.1 uses), with the FlowLM transformer's linear weights in Q8_0 and every other tensor in F16. The Mimi encoder, which turns audio into latents and is only used to clone a voice, is left out; in the release without voice cloning its weights are not usable anyway. Tensor names are those of the original model.safetensors.
Each file needs the tokenizer and voice embeddings of its language from Kyutai's repository, which are unchanged and not copied here, and the slower voice states in inklight-app/paced-voices load into the English one the same way.
How it was made
With quantize_model in goocy/pocket-tts-ios (branch aloud), a fork of the Rust port UnaMentis/pocket-tts-ios, which also loads the file. It is the same conversion the app used to run on each phone after downloading the original. Against the full-precision model, the transformer's hidden state differs by about 2 % (4.5 % in the worst frame of a 25-second utterance), and in listening tests the differences between renders followed the random seed, not the precision.
Credits and licence
This is an adaptation of Pocket TTS by Kyutai, licensed under the Creative Commons Attribution 4.0 International licence, and is released under the same licence. Kyutai's terms of use apply to it as to the original: it must not be used for voice impersonation or cloning without consent, to deceive, or to produce unlawful or harmful content.
Changes made: the transformer's linear weights were quantized to 8 bits, the other weights converted to 16-bit floats, and the voice-cloning encoder removed. Kyutai does not endorse these files or the apps. It is provided without warranty.
- Downloads last month
- 46
We're not able to determine the quantization variants.
Model tree for inklight-app/pocket-tts-q8
Base model
kyutai/pocket-tts-without-voice-cloning