Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use padmajabfrl/Gender-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use padmajabfrl/Gender-Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="padmajabfrl/Gender-Classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("padmajabfrl/Gender-Classification") model = AutoModelForSequenceClassification.from_pretrained("padmajabfrl/Gender-Classification") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3625e0c32543fa2745d97877a95d54e9f8263bf0538d71d8aa6f31ad47d9bf8e
- Size of remote file:
- 268 MB
- SHA256:
- 4cf8bed2338f116590fb6e8756ed73729ec6955997357afdb8c609d9ed4965f8
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