Instructions to use A-bhimany-u08/bert-base-cased-qqp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use A-bhimany-u08/bert-base-cased-qqp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="A-bhimany-u08/bert-base-cased-qqp")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("A-bhimany-u08/bert-base-cased-qqp") model = AutoModelForSequenceClassification.from_pretrained("A-bhimany-u08/bert-base-cased-qqp") - Notebooks
- Google Colab
- Kaggle
bert-base-cased model trained on quora question pair dataset. The task requires to predict whether the two given sentences (or questions) are not_duplicate (label 0) or duplicate (label 1). The model achieves 89% evaluation accuracy
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