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:
- aee5e472be479ab04e46b4640624d4e420d9dff37c203f61f5fd38e6a87a4417
- Size of remote file:
- 404 MB
- SHA256:
- 8ffa2e0c1fad3021108a839ac4464ced2443c026973ca16f485ce03522dcc151
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