Instructions to use MU-NLPC/whisper-tiny-audio-captioning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MU-NLPC/whisper-tiny-audio-captioning with Transformers:
# Load model directly from transformers import AutoProcessor, WhisperForAudioCaptioning processor = AutoProcessor.from_pretrained("MU-NLPC/whisper-tiny-audio-captioning") model = WhisperForAudioCaptioning.from_pretrained("MU-NLPC/whisper-tiny-audio-captioning") - Notebooks
- Google Colab
- Kaggle
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Minimal example:
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```
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# Load model
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architecture = "openai/whisper-tiny"
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checkpoint = "MU-NLPC/whiper-tiny-audio-captioning"
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Minimal example:
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```python
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# Load model
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architecture = "openai/whisper-tiny"
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checkpoint = "MU-NLPC/whiper-tiny-audio-captioning"
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