Instructions to use hf-internal-testing/tiny-random-Wav2Vec2Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Wav2Vec2Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-Wav2Vec2Model")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-Wav2Vec2Model") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-Wav2Vec2Model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 86cd25e4aa3758d9ecbc1298b0a3e2c8be9a995fd0aaad91a2cf331d7843cbb9
- Size of remote file:
- 115 kB
- SHA256:
- 79c390662ad9c494f33a3f615f8f211e8440ae75f0d3c1eec8622ab60bd22355
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