Instructions to use qfuxa/canary-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use qfuxa/canary-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir canary-mlx qfuxa/canary-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
Canary MLX
NVIDIA Canary ASR model converted to MLX format for Apple Silicon.
Usage
pip install canary-mlx
from canary_mlx import load_model
model = load_model("qfuxa/canary-mlx")
result = model.transcribe("audio.wav", language="en")
print(result)
Model Details
This model is a conversion of NVIDIA's Canary ASR model to Apple's MLX framework.
- Architecture: Conformer encoder + Transformer decoder
- Parameters: ~1B
- Supported Languages: 25 languages (see tags)
Original Model
Based on NVIDIA NeMo Canary model. See NVIDIA NeMo for the original implementation.
License
Model weights are released under CC-BY-4.0 license (same as original NVIDIA model).
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Hardware compatibility
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