Instructions to use hf-internal-testing/tiny-random-Wav2Vec2ConformerForXVector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Wav2Vec2ConformerForXVector with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForAudioXVector processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-Wav2Vec2ConformerForXVector") model = AutoModelForAudioXVector.from_pretrained("hf-internal-testing/tiny-random-Wav2Vec2ConformerForXVector", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5509849eecd3a3c2c00cec8842c34e5b2ff15d851566f0977e00e1f390a94636
- Size of remote file:
- 252 kB
- SHA256:
- a9a4b95ec99a31aeff4eeb04dd23cde70c73e182d5c499312a46cd05d4c38dd0
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