Instructions to use MU-NLPC/whisper-large-v2-audio-captioning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MU-NLPC/whisper-large-v2-audio-captioning with Transformers:
# Load model directly from transformers import AutoProcessor, WhisperForAudioCaptioning processor = AutoProcessor.from_pretrained("MU-NLPC/whisper-large-v2-audio-captioning") model = WhisperForAudioCaptioning.from_pretrained("MU-NLPC/whisper-large-v2-audio-captioning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 135 Bytes
297be36 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:1e6adc1993653de9983f5c703fb297a785097975c02daba7ee62a908c3f0324b
size 6173637880
|