Instructions to use cge7/wav2vec2-base-version3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cge7/wav2vec2-base-version3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="cge7/wav2vec2-base-version3")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("cge7/wav2vec2-base-version3") model = AutoModelForAudioClassification.from_pretrained("cge7/wav2vec2-base-version3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aee10136dbe739191bb183e36c0c1a99da7dcc091071f645725431334519ea7c
- Size of remote file:
- 4.6 kB
- SHA256:
- 1f01cb44a130a3402f922e27239876ed3146459d93397e53293b60fa05641664
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