Instructions to use vasista22/wav2vec2-360h-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vasista22/wav2vec2-360h-base with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForPreTraining processor = AutoProcessor.from_pretrained("vasista22/wav2vec2-360h-base") model = AutoModelForPreTraining.from_pretrained("vasista22/wav2vec2-360h-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6bb090b2eb8c73a6a187eee2a355c15f015da45408c7cefe726741a9f859e605
- Size of remote file:
- 380 MB
- SHA256:
- b9cccb05e0cca4d8c40d75ce2b84132350701c8d97934c8e0cfcae0f36b0ba82
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