Safetensors
MLX
mlx-audio
voxtral_realtime
speech-to-text
speech
transcription
asr
stt
4-bit precision
Instructions to use shreyask/voxtral-mini-4b-realtime-mlx-mixed-4-6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use shreyask/voxtral-mini-4b-realtime-mlx-mixed-4-6 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir voxtral-mini-4b-realtime-mlx-mixed-4-6 shreyask/voxtral-mini-4b-realtime-mlx-mixed-4-6
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
shreyask/voxtral-mini-4b-realtime-mlx-mixed-4-6
This model was converted to MLX format from shreyask/voxtral-mini-4b-realtime-mlx-fp16 using mlx-audio version 0.3.2.
Refer to the original model card for more details on the model.
Use with mlx-audio
pip install -U mlx-audio
CLI Example:
python -m mlx_audio.stt.generate --model shreyask/voxtral-mini-4b-realtime-mlx-mixed-4-6 --audio "audio.wav"
Python Example:
from mlx_audio.stt.utils import load_model
from mlx_audio.stt.generate import generate_transcription
model = load_model("shreyask/voxtral-mini-4b-realtime-mlx-mixed-4-6")
transcription = generate_transcription(
model=model,
audio_path="path_to_audio.wav",
output_path="path_to_output.txt",
format="txt",
verbose=True,
)
print(transcription.text)
- Downloads last month
- 7
Model size
1B params
Tensor type
F32
路
F16 路
U32 路
Hardware compatibility
Log In to add your hardware
4-bit
Inference Providers NEW
This model isn't deployed by any Inference Provider. 馃檵 Ask for provider support