Instructions to use rahulkhandelw/GenderPrediction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rahulkhandelw/GenderPrediction with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="rahulkhandelw/GenderPrediction")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("rahulkhandelw/GenderPrediction") model = AutoModelForTokenClassification.from_pretrained("rahulkhandelw/GenderPrediction") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 92799a97b44f2ef5627f2a98871672ee6cc72b6af6ebc91daacd48f51f3ea390
- Size of remote file:
- 265 MB
- SHA256:
- 3edbe3a8ea232e962fb74e240da828140bedf52b235da0c0149a0660e1d1ca94
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