Instructions to use superhands/go2-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Piper
How to use superhands/go2-models with Piper:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Pocket TTS ONNX and Whisper q5, Estonian
Browse files- README.md +58 -0
- SHA256SUMS +2 -0
- ggml-whisper-large-v3-turbo-et-verbatim-2604-q5_0.bin +3 -0
- pocket-cpp-et.tar.gz +3 -0
README.md
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license: cc-by-sa-4.0
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---
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---
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license: cc-by-sa-4.0
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language:
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- et
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tags:
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- text-to-speech
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- automatic-speech-recognition
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- onnx
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- whisper.cpp
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- robotics
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---
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# Go2 dock models
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Estonian speech models that Meridein's Unitree Go2 EDU docks run: the
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voice (Pocket TTS) and speech recognition (Whisper). Both are derived from
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public models, converted for the dock's Jetson. A dock downloads them at a
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pinned commit and checks each file's sha256 before using it.
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**Files are never overwritten here.** A new version gets a new file name, so
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a release that pins a commit and a sha256 keeps working.
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| file | what | size | sha256 |
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|---|---|---|---|
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| `pocket-cpp-et.tar.gz` | Pocket TTS, Estonian, as ONNX for PocketTTS.cpp (one folder, `pocket-cpp-et/`) | 436 064 256 | `1cf3ae8b3eab0724a023a8e5852272e0a870fccbd5fe7bc61a48940a680cd3ca` |
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| `ggml-whisper-large-v3-turbo-et-verbatim-2604-q5_0.bin` | Whisper large-v3-turbo, Estonian, q5_0 for whisper.cpp | 574 041 195 | `ec401581b6ac1788b4eff8b92c5257a65bf24b50be1e488387fd9760166a1ad7` |
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## `pocket-cpp-et.tar.gz`: Pocket TTS, Estonian (ONNX)
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- **Run by** [PocketTTS.cpp](https://github.com/VolgaGerm/PocketTTS.cpp) at
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`e801e7d`, with `--precision int8`. The int8 set is what runs; the fp32
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files are kept beside it.
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- **Made from** [cbentes/pocket-tts-estonian](https://huggingface.co/cbentes/pocket-tts-estonian):
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the weights and tokenizer at `e8d2fd9cc01ae6e4e505269adcc1d9bdaecbea0f`,
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the config and the six voice clips at
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`b37e49dd65514fb79a05cff2ace696e24af15d66`. Exported with pocket-tts
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2.1.0 and PocketTTS.cpp's `export_onnx.py` at `e801e7d`; the
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beginning-of-sequence before the voice is in `mimi_encoder.onnx`.
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`export_info.json` inside records the same.
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- **Licence:** CC BY-SA 4.0, as the weights it is made from, which were
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trained on the TalTech Estonian Speech Dataset 1.0. Credit:
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cbentes/pocket-tts-estonian and TalTech. Changes: converted to ONNX and
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quantised to int8. Share-alike: this derivative is under the same licence.
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## `ggml-whisper-large-v3-turbo-et-verbatim-2604-q5_0.bin`: Whisper, Estonian
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- **Run by** `whisper-server` ([whisper.cpp](https://github.com/ggml-org/whisper.cpp)),
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language `et`.
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- **Made from** [TalTechNLP/whisper-large-v3-turbo-et-verbatim-2604](https://huggingface.co/TalTechNLP/whisper-large-v3-turbo-et-verbatim-2604),
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its ggml model (`ggml/ggml-model.bin`, sha256 `4e231f931f029850d7ca497efe4223f85c495a27d986d955f9a577ac1cd02edb`),
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quantised to `q5_0` with whisper.cpp's quantize tool (whisper.cpp
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`60c0be6`). The quantised model needs about 1 GB less memory.
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- **Licence:** that of TalTechNLP's model, which this file is derived from.
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See their model card; credit: TalTech (Tallinn University of Technology).
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The repository's `cc-by-sa-4.0` tag is the Pocket model's.
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## Checking a download
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```bash
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sha256sum -c SHA256SUMS
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```
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1cf3ae8b3eab0724a023a8e5852272e0a870fccbd5fe7bc61a48940a680cd3ca pocket-cpp-et.tar.gz
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ec401581b6ac1788b4eff8b92c5257a65bf24b50be1e488387fd9760166a1ad7 ggml-whisper-large-v3-turbo-et-verbatim-2604-q5_0.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:ec401581b6ac1788b4eff8b92c5257a65bf24b50be1e488387fd9760166a1ad7
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size 574041195
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pocket-cpp-et.tar.gz
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version https://git-lfs.github.com/spec/v1
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oid sha256:1cf3ae8b3eab0724a023a8e5852272e0a870fccbd5fe7bc61a48940a680cd3ca
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size 436064256
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