Instructions to use hf-tiny-model-private/tiny-random-Data2VecAudioForXVector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-Data2VecAudioForXVector with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForAudioXVector tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-Data2VecAudioForXVector") model = AutoModelForAudioXVector.from_pretrained("hf-tiny-model-private/tiny-random-Data2VecAudioForXVector") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 91bcc309d0f8cda0013f0ff9d9f0147b80d8851c82feac7bb07946956b8539d1
- Size of remote file:
- 318 kB
- SHA256:
- 6645df55cf024170b1c58a68e61d4005fa7f7bf051476bfbecfe002318b66f19
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.