Instructions to use hf-tiny-model-private/tiny-random-WavLMForXVector 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-WavLMForXVector with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForAudioXVector processor = AutoProcessor.from_pretrained("hf-tiny-model-private/tiny-random-WavLMForXVector") model = AutoModelForAudioXVector.from_pretrained("hf-tiny-model-private/tiny-random-WavLMForXVector") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fea3a0e3f77f5c250efb8b8d95e0295da1de8bc3456c265ae1bebddae01650df
- Size of remote file:
- 162 kB
- SHA256:
- 44d417e21ef49704240fc9f6590fe5a3d5968dd4cf380c9212c183f0fc6d5170
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