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:
- 5d08137c742394ddd74ad7f92338c898094eeb30dfc5002542c6e5b12c7fe84f
- Size of remote file:
- 895 kB
- SHA256:
- 6ab78fae3b6c5bf8ba81084bfc87f5fa52fd84c44905c614e1e283d6c373d401
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