Instructions to use doggy8088/Breeze-ASR-26-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use doggy8088/Breeze-ASR-26-MLX with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Breeze-ASR-26-MLX doggy8088/Breeze-ASR-26-MLX
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
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Download README.md from doggy8088/Breeze-ASR-26-MLX: direct link, hf CLI and curl.
- Browser
- Download file 981 Bytes
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https://huggingface.co/doggy8088/Breeze-ASR-26-MLX/resolve/main/README.md
- Command line
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hf download hf://doggy8088/Breeze-ASR-26-MLX/README.md
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curl -L -o README.md https://huggingface.co/doggy8088/Breeze-ASR-26-MLX/resolve/main/README.md
981 Bytes
| license: apache-2.0 | |
| library_name: mlx | |
| pipeline_tag: automatic-speech-recognition | |
| base_model: MediaTek-Research/Breeze-ASR-26 | |
| tags: | |
| - mlx | |
| - mlx-whisper | |
| - whisper | |
| - automatic-speech-recognition | |
| - taiwanese-hokkien | |
| - taigi | |
| - zh | |
| - nan | |
| # Breeze-ASR-26-MLX | |
| 這是 [MediaTek-Research/Breeze-ASR-26](https://huggingface.co/MediaTek-Research/Breeze-ASR-26) 的 MLX 轉換版本。原始模型是以 Whisper Large-v2 為基礎微調的語音辨識模型。 | |
| ## 使用方式 | |
| 安裝 `mlx-whisper`: | |
| ```bash | |
| pip install mlx-whisper | |
| ``` | |
| 使用 CLI 轉錄音訊: | |
| ```bash | |
| mlx_whisper audio.wav --model doggy8088/Breeze-ASR-26-MLX --language zh | |
| ``` | |
| 或在 Python 中使用: | |
| ```python | |
| import mlx_whisper | |
| result = mlx_whisper.transcribe( | |
| "audio.wav", | |
| path_or_hf_repo="doggy8088/Breeze-ASR-26-MLX", | |
| language="zh", | |
| ) | |
| print(result["text"]) | |
| ``` | |
| ## 轉換方式 | |
| 此模型是從 Hugging Face Transformers checkpoint 轉換成 `mlx-whisper` 格式,權重使用 fp16。 | |