Automatic Speech Recognition
Safetensors
MLX
mlx-audio-plus
whisper
speech-recognition
speech-to-text
stt
Instructions to use mlx-community/whisper-large-v3-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/whisper-large-v3-4bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir whisper-large-v3-4bit mlx-community/whisper-large-v3-4bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
mlx-community/whisper-large-v3-4bit
This model was converted to MLX format from openai/whisper-large-v3 using mlx-audio-plus version 0.1.4.
Use with mlx-audio-plus
pip install -U mlx-audio-plus
Command line
mlx_audio.stt --model mlx-community/whisper-large-v3-4bit --audio audio.mp3
Python
from mlx_audio.stt import transcribe
result = transcribe(
audio="audio.mp3",
model="mlx-community/whisper-large-v3-4bit",
)
print(result["text"])
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Hardware compatibility
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Quantized
Model tree for mlx-community/whisper-large-v3-4bit
Base model
openai/whisper-large-v3