Instructions to use MU-NLPC/whisper-small-audio-captioning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MU-NLPC/whisper-small-audio-captioning with Transformers:
# Load model directly from transformers import AutoProcessor, WhisperForAudioCaptioning processor = AutoProcessor.from_pretrained("MU-NLPC/whisper-small-audio-captioning") model = WhisperForAudioCaptioning.from_pretrained("MU-NLPC/whisper-small-audio-captioning") - Notebooks
- Google Colab
- Kaggle
Update model_class.py
#5
by geekweilai - opened
Hi, there.
I meet an error that the WhisperForAudioCaptioning.forward() method is receiving an unexpected keyword argument decoder_position_ids.
This argument is not defined in the forward() method of the WhisperForAudioCaptioning class. To fix this issue, I modify the forward() method of the WhisperForAudioCaptioning class to accept decoder_position_ids as an argument.
Waiting for your reply.
Hi,
Thank you for your contribution.
The decoder_position_ids parameter didn't exist in transformers.WhisperForConditionalGeneration at the time we wrote this code.
The change seems good to me, I'm merging it. Thanks.
prompteus changed pull request status to merged