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
Adding `safetensors` variant of this model
#4
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:6e63b89268c3c40c12730fc2c8ea1bb94789738fd1520f645368124e59c3cd69
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size 151061672
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