Instructions to use Shobhank-iiitdwd/Distilroberta-base-QQP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shobhank-iiitdwd/Distilroberta-base-QQP with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Shobhank-iiitdwd/Distilroberta-base-QQP")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Shobhank-iiitdwd/Distilroberta-base-QQP") model = AutoModelForSequenceClassification.from_pretrained("Shobhank-iiitdwd/Distilroberta-base-QQP") - Notebooks
- Google Colab
- Kaggle
Training Data
This model was trained on the Quora Duplicate Questions dataset. The model will predict a score between 0 and 1 how likely the two given questions are duplicates.
Note: The model is not suitable to estimate the similarity of questions, e.g. the two questions "How to learn Java" and "How to learn Python" will result in a rahter low score, as these are not duplicates.
Usage and Performance
Pre-trained models can be used like this:
from sentence_transformers import CrossEncoder
model = CrossEncoder('model_name')
scores = model.predict([('Question 1', 'Question 2'), ('Question 3', 'Question 4')])
You can use this model also without sentence_transformers and by just using Transformers AutoModel class
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