Instructions to use MERaLiON/MERaLiON-2-10B-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use MERaLiON/MERaLiON-2-10B-MLX with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir MERaLiON-2-10B-MLX MERaLiON/MERaLiON-2-10B-MLX
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
docs: add batch_transcribe example to MLX section
#6
by SiruiHe - opened
README.md
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@@ -607,6 +607,20 @@ text = transcribe(model, "audio.wav", task="sqa", question="What is the speaker
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text = transcribe(model, "audio.wav", task="summarize")
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```
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#### CLI
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```bash
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text = transcribe(model, "audio.wav", task="summarize")
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```
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#### Batch Inference
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Process multiple audio files in parallel for higher throughput:
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```python
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from mlx_meralion import load_model, batch_transcribe
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model = load_model("MERaLiON/MERaLiON-2-10B-MLX")
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results = batch_transcribe(model, ["audio1.wav", "audio2.wav", "audio3.wav"])
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for text in results:
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print(text)
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```
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#### CLI
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```bash
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