Instructions to use kming/unispeech-sat-base-plus-sv-finetuned-ami-ten-percent-train with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kming/unispeech-sat-base-plus-sv-finetuned-ami-ten-percent-train with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForAudioXVector processor = AutoProcessor.from_pretrained("kming/unispeech-sat-base-plus-sv-finetuned-ami-ten-percent-train") model = AutoModelForAudioXVector.from_pretrained("kming/unispeech-sat-base-plus-sv-finetuned-ami-ten-percent-train") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5211f4cc9e6305409a7572293dea9f1938227c5fa7b9ffd0ea50b13fce546597
- Size of remote file:
- 4.09 kB
- SHA256:
- 7369b934f51a9122e7dc3c2f3d8e472d0cc9601c027499b8dd47b3c857c96b1e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.