{ "cells": [ { "cell_type": "markdown", "id": "104bbe82", "metadata": {}, "source": [ "# Cross-Encoder for Quora Duplicate Questions Detection\n", "This model was trained using [SentenceTransformers](https://sbert.net) [Cross-Encoder](https://www.sbert.net/examples/applications/cross-encoder/README.html) class.\n" ] }, { "cell_type": "markdown", "id": "71def254", "metadata": {}, "source": [ "## Training Data\n", "This model was trained on the [Quora Duplicate Questions](https://www.quora.com/q/quoradata/First-Quora-Dataset-Release-Question-Pairs) dataset. The model will predict a score between 0 and 1 how likely the two given questions are duplicates.\n" ] }, { "cell_type": "markdown", "id": "10f2b17c", "metadata": {}, "source": [ "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.\n" ] }, { "cell_type": "markdown", "id": "9e28c83a", "metadata": {}, "source": [ "## Usage and Performance\n" ] }, { "cell_type": "markdown", "id": "bc8ce622", "metadata": {}, "source": [ "Pre-trained models can be used like this:\n" ] }, { "cell_type": "code", "execution_count": null, "id": "3f66406a", "metadata": {}, "outputs": [], "source": [ "!pip install --upgrade paddlenlp" ] }, { "cell_type": "code", "execution_count": null, "id": "7ba92b4f", "metadata": {}, "outputs": [], "source": [ "import paddle\n", "from paddlenlp.transformers import AutoModel\n", "\n", "model = AutoModel.from_pretrained(\"cross-encoder/quora-distilroberta-base\")\n", "input_ids = paddle.randint(100, 200, shape=[1, 20])\n", "print(model(input_ids))" ] }, { "cell_type": "markdown", "id": "93656328", "metadata": {}, "source": [ "> The model introduction and model weights originate from [https://huggingface.co/cross-encoder/quora-distilroberta-base](https://huggingface.co/cross-encoder/quora-distilroberta-base) and were converted to PaddlePaddle format for ease of use in PaddleNLP.\n" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.13" } }, "nbformat": 4, "nbformat_minor": 5 }