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:
- bdd0cbad2b4e57c937282875361963fbe8fc64af55352a3080e74bb0053f3b11
- Size of remote file:
- 378 MB
- SHA256:
- 76c0395ae195c8dcc9cf4758a5ef16902932b9370d8e967b361b333509e10376
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