Skip to page content
SAVRN
Search Plan a project

Open-weight model · Text to speech

nanobot-channel-voice-models

by iChizer0 iChizer0/nanobot-channel-voice-models

nanobot-channel-voice-models is an open-weight model for text to speech from iChizer0, released under other. Its published files total 1.2 GB.

RKNN model artifacts and a checksum-pinned weights index for nanobot-channel-voice.

Parameters—
Context—
Weights5.6 MB
Licenseother
AccessOpen weights
Monthly Downloads—

Model Card

RKNN model artifacts and a checksum-pinned weights index for nanobot-channel-voice. The repository includes four official openWakeWord phrase heads, each available as an original-ONNX package for CPU/ONNX-capable hosts and as a validated RV1126B hybrid package: Choose one variant for the target host. Every fetch is a complete package: ONNX entries install the three original upstream graphs plus a phrase sidecar; RV1126B entries install the phrase head, exact Python-mel filterbank, and static RKNN embedding. The runtime fetches a complete model entry through nanobot-voice: weights-index.json is the authoritative manifest of available keys, source provenance, checksums, and acceptance…

Excerpt from the card by iChizer0, licensed other.

Identity and Version

Repository
iChizer0/nanobot-channel-voice-models
Publisher
iChizer0
Task
Text to speech
Modality
Audio
Library
Not stated by the source
Parameters
Not stated by the source
Languages
Not stated by the source
Revision
61a0a0ce770466bfa0e1d628cf36d46173794065
First published
2026-08-17
Last updated
2026-09-24

Files and Weights

57 files, 1.2 GB in total. The weights are 6 files totalling 5.6 MB in onnx.

Weights6 files · 5.6 MB
Configuration13 files · 62.1 KB
Tokenizer1 file · 816.7 KB
Documentation5 files · 54.0 KB
Other31 files · 1.2 GB
Repository1 file · 3.3 KB
Every file
FileTypeSizeSHA-256
models/wake/_shared/openwakeword/v0.5.1/embedding_model.onnxWeights1.3 MB 70d164290c1d
models/wake/_shared/openwakeword/v0.5.1/melspectrogram.onnxWeights1.1 MB ba2b0e0f8b7b
models/wake/openwakeword/alexa/onnx/model.onnxWeights854.2 KB 6ff566a01d12
models/wake/openwakeword/hey-jarvis/onnx/model.onnxWeights1.3 MB 94a13cfe6007
models/wake/openwakeword/hey-mycroft/onnx/model.onnxWeights857.7 KB c2a311e8fa13
models/wake/openwakeword/hey-rhasspy/onnx/model.onnxWeights204.1 KB 5a9b3ed3be29
models/stt/sensevoice/small/rknn.rv1126b/frontend.jsonConfiguration13.4 KB —
models/stt/zipformer/zh-en/rknn.rv1126b/meta.jsonConfiguration3.9 KB —
models/tts/matcha/zh-CN/baker/rknn.rv1126b/meta.jsonConfiguration95 B —
models/tts/matcha/zh-en/icefall/rknn.rv1126b/meta.jsonConfiguration365 B —
models/wake/openwakeword/alexa/onnx/meta.jsonConfiguration1.7 KB —
models/wake/openwakeword/alexa/rknn.rv1126b/meta.jsonConfiguration1.6 KB —
models/wake/openwakeword/hey-jarvis/onnx/meta.jsonConfiguration1.7 KB —
models/wake/openwakeword/hey-jarvis/rknn.rv1126b/meta.jsonConfiguration1.6 KB —
models/wake/openwakeword/hey-mycroft/onnx/meta.jsonConfiguration1.7 KB —
models/wake/openwakeword/hey-mycroft/rknn.rv1126b/meta.jsonConfiguration2.0 KB —
models/wake/openwakeword/hey-rhasspy/onnx/meta.jsonConfiguration1.7 KB —
models/wake/openwakeword/hey-rhasspy/rknn.rv1126b/meta.jsonConfiguration1.6 KB —
weights-index.jsonConfiguration30.8 KB —
MIGRATION.mdDocumentation1.5 KB —
OPENWAKEWORD_WEIGHTS_LAYOUT.mdDocumentation6.8 KB —
README.mdDocumentation4.9 KB —
models/README.mdDocumentation4.8 KB —
models/tts/matcha/zh-en/icefall/rknn.rv1126b/espeak-ng-data.LICENSE.txtDocumentation36.1 KB —
models/stt/sensevoice/small/rknn.rv1126b/model.rknnOther486.6 MB 72b8665fb6c9
models/stt/sensevoice/small/rknn.rv1126b/tokens.txtOther315.9 KB —
models/stt/whisper/base/rknn.rv1126b/decoder.rknnOther158.9 MB 1b511485f809
models/stt/whisper/base/rknn.rv1126b/encoder.rknnOther42.6 MB 55b89e16a2cc
models/stt/whisper/base/rknn.rv1126b/mel_filters.txtOther402.0 KB —
models/stt/zipformer/zh-en/rknn.rv1126b/decoder.rknnOther8.0 MB 35d0262bea0b
models/stt/zipformer/zh-en/rknn.rv1126b/encoder.rknnOther140.0 MB 1976bdf22c00
models/stt/zipformer/zh-en/rknn.rv1126b/joiner.rknnOther6.5 MB 3449fdbf0f5c
models/stt/zipformer/zh-en/rknn.rv1126b/tokens.txtOther56.3 KB —
models/tts/_shared/vocoder/vocos-22khz-univ/rknn.rv1126b/mels-80x800/vocoder.rknnOther27.8 MB a0584c68c932
models/tts/matcha/en-US/ljspeech/rknn.rv1126b/decoder.rknnOther59.6 MB 331d76d2c071
models/tts/matcha/en-US/ljspeech/rknn.rv1126b/encoder.rknnOther16.4 MB cd49011e0b7e
models/tts/matcha/en-US/ljspeech/rknn.rv1126b/tokens.txtOther954 B —
models/tts/matcha/zh-CN/baker/rknn.rv1126b/decoder.rknnOther59.6 MB fa3cf91ad885
models/tts/matcha/zh-CN/baker/rknn.rv1126b/encoder.rknnOther17.2 MB 4b1b3c366411
models/tts/matcha/zh-CN/baker/rknn.rv1126b/lexicon.txtOther1.4 MB —
models/tts/matcha/zh-CN/baker/rknn.rv1126b/tokens.txtOther19.6 KB —
models/tts/matcha/zh-en/icefall/rknn.rv1126b/decoder.rknnOther59.6 MB 9731108c314c
models/tts/matcha/zh-en/icefall/rknn.rv1126b/encoder.rknnOther17.2 MB f9e3e76fcc27
models/tts/matcha/zh-en/icefall/rknn.rv1126b/espeak-ng-data.tar.bz2Other7.3 MB 00ab74bba5d7
models/tts/matcha/zh-en/icefall/rknn.rv1126b/lexicon.txtOther1.4 MB —
models/tts/matcha/zh-en/icefall/rknn.rv1126b/tokens.txtOther21.1 KB —
models/tts/matcha/zh-en/icefall/rknn.rv1126b/vocoder.rknnOther27.8 MB b2c7edf4404c
models/tts/mms/en/rknn.rv1126b/decoder.rknnOther44.9 MB 7c1fbd8e0817
models/tts/mms/en/rknn.rv1126b/encoder.rknnOther21.1 MB 2c6ccd8dbfef
models/vad/firered/streaming/rknn.rv1126b/cmvn.arkOther1.3 KB —
models/vad/firered/streaming/rknn.rv1126b/model.rknnOther1.5 MB 08bcadf31ec0
models/vad/silero/v6/rknn.rv1126b/model.rknnOther2.0 MB 9262e63ae97b
models/vad/smartturn/v3.2/rknn.rv1126b/model.rknnOther17.0 MB 617992e2ee2b
models/wake/_shared/openwakeword/v0.5.1/mel_filters.npyOther33.0 KB 65e9e696738d
models/wake/_shared/openwakeword/v0.5.1/rknn.rv1126b/embedding.rknnOther791.9 KB 1be254f5328d
.gitattributesRepository3.3 KB —
models/stt/whisper/base/rknn.rv1126b/vocab.tiktokenTokenizer816.7 KB —

License and Download

License
other
Access
Open weights, no gate
Download size
5.6 MB
Download from iChizer0

Released by iChizer0 through its official repository on Hugging Face.

Memory Requirements

PrecisionWeights in memory
As published5.6 MB

Weights only, from the published parameter count; the key-value cache and runtime add to this.

Questions About nanobot-channel-voice-models

What license is nanobot-channel-voice-models released under?

other, as its publisher declares it. Read the license text before commercial use.

Similar Models

Model · Text to speech

Kokoro-82M

Hexgrad

Kokoro is an open-weight TTS model with 82 million parameters. Despite its lightweight architecture, it delivers comparable quality to larger models while being significantly faster and more cost-efficient. With Apache-licensed weights, Kokoro can be deployed anywhere from production environments to personal projects. You can run this basic cell on Google Colab. Listen to samples. For more languages and details, see Advanced Usage. Under the hood, kokoro uses misaki, a G2P library at https://github.com/hexgrad/misaki Model SHA256 Hash: 496dba118d1a58f5f3db2efc88dbdc216e0483fc89fe6e47ee1f2c53f18ad1e4 Data: Kokoro was trained exclusively on permissive/non-copyrighted audio data and IPA…

Open weights apache-2.0

Model · Text to speech

audio.cpp-gguf

Audio.cpp

This directory contains audio.cpp-native GGUF conversions of multiple speech models. These files are intended for use with audio.cpp. If you enjoy the project, please star audio.cpp on GitHub and this Hugging Face repository. For conversion details, supported layouts, direct-file loading, sidecar embedding, and the latest compatibility notes, see the audio.cpp GGUF guide: - https://github.com/0xShug0/audio.cpp/blob/main/docs/gguf.md!!! Converted and quantized packages are checked with automated metrics, but perceived quality can still differ for human listeners. Please validate the exact package, backend, and route to confirm the output is acceptable for your use case. The table lists the…

Open weights other audio.cpp

Model · Text to speech

XTTS-v2

Coqui.ai

ⓍTTS is a Voice generation model that lets you clone voices into different languages by using just a quick 6-second audio clip. There is no need for an excessive amount of training data that spans countless hours. This is the same or similar model to what powers Coqui Studio and Coqui API. - Supports 17 languages. - Voice cloning with just a 6-second audio clip. - Emotion and style transfer by cloning. - Cross-language voice cloning. - Multi-lingual speech generation. - 24khz sampling rate. - 2 new languages; Hungarian and Korean - Architectural improvements for speaker conditioning. - Enables the use of multiple speaker references and interpolation between speakers. - Stability…

Open weights other coqui

Model · Text to speech

chatterbox

Resemble AI

Chatterbox Multilingual V3 is the latest general-purpose multilingual TTS model in the Chatterbox family. It keeps the same 0.5B model size while improving speaker similarity, reducing hallucinations, and producing more natural, conversational speech across languages. V3 is designed for broad language coverage like V2, but with stronger stability and more expressive generation. It is the recommended multilingual model for users who want one voice cloning model that works across many languages. Try it in the Chatterbox Multilingual TTS V3 Space. Alongside V3, we are releasing the Single Language Pack: dedicated finetunes for priority languages where tighter quality control, stronger…

Open weights mit chatterbox

Model · Text to speech

F5-TTS

Yushen CHEN

Download F5-TTS or E2 TTS and place under ckpts/ Paper: F5-TTS: A Fairytaler that Fakes Fluent and Faithful Speech with Flow Matching

Open weights cc-by-nc-4.0 f5-tts

Model · Text to speech

Kokoro-82M-v1.0-ONNX

ONNX Community

Kokoro is a frontier TTS model for its size of 82 million parameters (text in/audio out). First, install the kokoro-js library from NPM using: You can then generate speech as follows: Optionally, save the audio to a file: The model is resilient to quantization, enabling efficient high-quality speech synthesis at a fraction of the original model size.

Open weights apache-2.0 transformers.js