Automatic Speech Recognition
MLX
Safetensors
moss_transcribe_diarize
int8
speaker-diarization
custom_code
Instructions to use plaincompute/mlx-MOSS-Transcribe-Diarize-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use plaincompute/mlx-MOSS-Transcribe-Diarize-8bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir mlx-MOSS-Transcribe-Diarize-8bit plaincompute/mlx-MOSS-Transcribe-Diarize-8bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
| license: apache-2.0 | |
| library_name: mlx | |
| tags: | |
| - mlx | |
| - int8 | |
| - automatic-speech-recognition | |
| - speaker-diarization | |
| base_model: | |
| - vanch007/mlx-MOSS-Transcribe-Diarize | |
| pipeline_tag: automatic-speech-recognition | |
| # mlx-MOSS-Transcribe-Diarize 8bit | |
| 8bit MLX weight-only quantized variant of `vanch007/mlx-MOSS-Transcribe-Diarize`. | |
| Quantization uses MLX affine quantization with `bits=8` and `group_size=64` on the text backbone, excluding the Whisper audio encoder and VQ adaptor. | |
| ```bash | |
| python -m moss_transcribe_diarize.mlx.cli /path/to/input.wav \ | |
| --model plaincompute/mlx-MOSS-Transcribe-Diarize-8bit \ | |
| --out-dir runs/mlx_8bit_example | |
| ``` | |