Instructions to use cge7/wav2vec2-base-version2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cge7/wav2vec2-base-version2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="cge7/wav2vec2-base-version2")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("cge7/wav2vec2-base-version2") model = AutoModelForAudioClassification.from_pretrained("cge7/wav2vec2-base-version2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9f48dda2783bf39ff70e19c56b160160a8986113c134d39220061def2be19c62
- Size of remote file:
- 4.6 kB
- SHA256:
- b8974aa377a64d9f589c6b4beb648b512016928a2ca390461d018a027e6b5d68
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