Instructions to use hf-internal-testing/tiny-random-Wav2Vec2ConformerModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Wav2Vec2ConformerModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-Wav2Vec2ConformerModel")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-Wav2Vec2ConformerModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-Wav2Vec2ConformerModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 31997b9b6059e58e512a439c85f28c2e44ee5fcf2d267d197d73099f484ca152
- Size of remote file:
- 162 kB
- SHA256:
- f146307182d7151a242a79fc6742a44a0ba78160bec8aab4dcb3ee3f6b91075f
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