Automatic Speech Recognition
Safetensors
MLX
mlx-audio
moss_transcribe_diarize
speaker-diarization
timestamps
custom_code
8-bit precision
Instructions to use kuotient/MOSS-Transcribe-Diarize-MLX-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use kuotient/MOSS-Transcribe-Diarize-MLX-8bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir MOSS-Transcribe-Diarize-MLX-8bit kuotient/MOSS-Transcribe-Diarize-MLX-8bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
MOSS-Transcribe-Diarize — MLX 8-bit
8-bit MLX quantization of OpenMOSS-Team/MOSS-Transcribe-Diarize (0.9B end-to-end transcription + speaker diarization + timestamps).
- Quantization: affine 8-bit, group size 64, text backbone only — the Whisper encoder and the VQ adaptor stay full precision (quantizing the encoder's positional embedding breaks the feature broadcast).
- Quality: byte-identical transcripts to the bf16 reference across Korean, Korean↔English code-switching, and multi-speaker English in our checks.
- Load:
mlx-audio/mlx-audio-swiftviafromModelDirectory.
Original model © the OpenMOSS / MOSI.AI team, Apache-2.0. This repository only re-hosts a quantized copy for reproducible on-device deployment.
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Model size
0.6B params
Tensor type
BF16
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U32 ·
Hardware compatibility
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8-bit
Model tree for kuotient/MOSS-Transcribe-Diarize-MLX-8bit
Base model
OpenMOSS-Team/MOSS-Transcribe-Diarize