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:
- 2213626399a4223e8ea96cad076822dc53d2af58ae44d13eec3436f5df5a4c82
- Size of remote file:
- 3.39 kB
- SHA256:
- a0b6580de9ac8660ce03e0e19d9860f796bbbf64ea27b4404b54ea3b4eb1ff25
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