Instructions to use kming/wav2vec2-base-superb-sv-finetuned-ami-ten-percent-train-new with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kming/wav2vec2-base-superb-sv-finetuned-ami-ten-percent-train-new with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForAudioXVector processor = AutoProcessor.from_pretrained("kming/wav2vec2-base-superb-sv-finetuned-ami-ten-percent-train-new") model = AutoModelForAudioXVector.from_pretrained("kming/wav2vec2-base-superb-sv-finetuned-ami-ten-percent-train-new") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b8383b92ee08a7d98ceed3aa636e2c973153b19f0cacf796b8fd2ac53174c92f
- Size of remote file:
- 4.09 kB
- SHA256:
- 12a321e5786f5198becd9616e6af7795b318cc73de2ae3f4903b1b50b47aa80f
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