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:
- 57e05cf72829e5c6b0681c956f5de02800d5325d83042cf610c04f4d679a8307
- Size of remote file:
- 3.9 kB
- SHA256:
- 29d3258e559db8486bb5f6344def11583cdd25ecbd9f9cf435139141b517e3fd
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