Instructions to use Isma/v2_405k_all with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Isma/v2_405k_all with Transformers:
# Load model directly from transformers import AutoProcessor, Wav2Vec2ForPreTrainingWithMixupV2 processor = AutoProcessor.from_pretrained("Isma/v2_405k_all") model = Wav2Vec2ForPreTrainingWithMixupV2.from_pretrained("Isma/v2_405k_all", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4cd9299fe772999905b5422b6a5124e652ef9684a176137babef258550ef8753
- Size of remote file:
- 381 MB
- SHA256:
- 33fe5411a5b997f1cd49c7c8ad73c23d2f0208cff2c5c7542d4e75c400559f21
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