Instructions to use hts98/gender_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hts98/gender_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="hts98/gender_classification")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("hts98/gender_classification") model = AutoModelForAudioClassification.from_pretrained("hts98/gender_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ae5e9a4901877d3a51e49de7d2e0f1d90757ddd4f41dee929a7a089a9232ffde
- Size of remote file:
- 3.9 kB
- SHA256:
- 34595a5dd45ed59381ab3891e7dc1780f448d1391cda78482ebfc2b38fedb6eb
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