Instructions to use facebook/wav2vec2-conformer-rope-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/wav2vec2-conformer-rope-large with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForPreTraining processor = AutoProcessor.from_pretrained("facebook/wav2vec2-conformer-rope-large") model = AutoModelForPreTraining.from_pretrained("facebook/wav2vec2-conformer-rope-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c04ebdd78731b0cb3d4052f7f0ea85b5f3e0c7d74b84923bef477bbd49bbe2c0
- Size of remote file:
- 2.38 GB
- SHA256:
- 3b445a10fd893326064c377586fdb0f1c8a0f28ed3916ecfb234563149e60565
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