Instructions to use hf-tiny-model-private/tiny-random-Wav2Vec2ConformerForXVector 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-Wav2Vec2ConformerForXVector with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForAudioXVector processor = AutoProcessor.from_pretrained("hf-tiny-model-private/tiny-random-Wav2Vec2ConformerForXVector") model = AutoModelForAudioXVector.from_pretrained("hf-tiny-model-private/tiny-random-Wav2Vec2ConformerForXVector") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f73fee89a5856bc81aaf2607632135b7795848911133cd2d233d1e70549b4fd0
- Size of remote file:
- 252 kB
- SHA256:
- b74e4f335aedde64406dd863ab3e661ac752c495c64cbc8de929369060786fae
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