Instructions to use hf-internal-testing/tiny-random-Wav2Vec2ConformerForPreTraining with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Wav2Vec2ConformerForPreTraining with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForPreTraining processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-Wav2Vec2ConformerForPreTraining") model = AutoModelForPreTraining.from_pretrained("hf-internal-testing/tiny-random-Wav2Vec2ConformerForPreTraining") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 93f4a4df2109727723b40068f697a2ef0a07e07f12b71b4a051fc7ce4b789fbe
- Size of remote file:
- 859 kB
- SHA256:
- 3b6898c5b16c8b55b4fad41f12b5c17f1a2dce6e89238f92021ba6ea8705118a
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