Instructions to use IPEVO/whisperkit-coreml with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- WhisperKit
How to use IPEVO/whisperkit-coreml with WhisperKit:
# Install CLI with Homebrew on macOS device brew install whisperkit-cli # View all available inference options whisperkit-cli transcribe --help # Download and run inference using whisper base model whisperkit-cli transcribe --audio-path /path/to/audio.mp3 # Or use your preferred model variant whisperkit-cli transcribe --model "large-v3" --model-prefix "distil" --audio-path /path/to/audio.mp3 --verbose
- Notebooks
- Google Colab
- Kaggle
File size: 1,008 Bytes
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license: apache-2.0
base_model: MediaTek-Research/Breeze-ASR-26
tags:
- whisperkit
- coreml
- automatic-speech-recognition
- taiwanese-hokkien
---
# IPEVO WhisperKit CoreML Models
WhisperKit-compatible Core ML models used by [Vurbo.ai](https://vurbo.ai). Converted with
[argmaxinc/whisperkittools](https://github.com/argmaxinc/whisperkittools).
## Models
| Folder | Base model | Precision | Size | Notes |
|--------|-----------|-----------|------|-------|
| `breeze-asr-26-q8` | [MediaTek-Research/Breeze-ASR-26](https://huggingface.co/MediaTek-Research/Breeze-ASR-26) | 8-bit palettized | ~1.5GB | Taiwanese Hokkien (台語) ASR, outputs Traditional Chinese |
## Attribution
`breeze-asr-26-q8` is a derivative of Breeze-ASR-26 by MediaTek Research
(Apache License 2.0), quantized to 8-bit and converted to Core ML for on-device
inference via WhisperKit. `config.json` / `tokenizer.json` are from
[openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) (same vocabulary).
|