Automatic Speech Recognition
Safetensors
MLX
mlx-audio-plus
whisper
speech-recognition
speech-to-text
stt
Instructions to use mlx-community/whisper-base-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/whisper-base-4bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir whisper-base-4bit mlx-community/whisper-base-4bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
metadata
library_name: mlx-audio-plus
license: apache-2.0
base_model:
- openai/whisper-base
tags:
- mlx
- whisper
- speech-recognition
- speech-to-text
- stt
pipeline_tag: automatic-speech-recognition
mlx-community/whisper-base-4bit
This model was converted to MLX format from openai/whisper-base 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-base-4bit --audio audio.mp3
Python
from mlx_audio.stt import transcribe
result = transcribe(
audio="audio.mp3",
model="mlx-community/whisper-base-4bit",
)
print(result["text"])