Audio Classification
Transformers
PyTorch
English
wav2vec2
pretraining
non-verbal-vocalization
baby-crying
Instructions to use alkiskoudounas/voc2vec with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alkiskoudounas/voc2vec with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="alkiskoudounas/voc2vec")# Load model directly from transformers import AutoProcessor, AutoModelForPreTraining processor = AutoProcessor.from_pretrained("alkiskoudounas/voc2vec") model = AutoModelForPreTraining.from_pretrained("alkiskoudounas/voc2vec", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 71086101ce600855ea102c1f32cb736c99caa895564e2498cc8425c13f623ecd
- Size of remote file:
- 380 MB
- SHA256:
- 67d61add299b8f9b52dc2ea197690ba4b00cc27dca787ec756c21c8da6f781c6
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