{ "cells": [ { "cell_type": "markdown", "id": "a3deebdc", "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": "4fc17643", "metadata": {}, "source": [ "## Training Data\n", "This model was trained on the [STS benchmark dataset](http://ixa2.si.ehu.eus/stswiki/index.php/STSbenchmark). The model will predict a score between 0 and 1 how for the semantic similarity of two sentences.\n" ] }, { "cell_type": "markdown", "id": "f66fb11e", "metadata": {}, "source": [ "## Usage and Performance\n" ] }, { "cell_type": "markdown", "id": "fd12128b", "metadata": {}, "source": [ "Pre-trained models can be used like this:\n" ] }, { "cell_type": "code", "execution_count": null, "id": "d0d04e39", "metadata": {}, "outputs": [], "source": [ "!pip install --upgrade paddlenlp" ] }, { "cell_type": "code", "execution_count": 1, "id": "d07e31aa", "metadata": { "collapsed": true }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/root/miniconda3/envs/paddle/lib/python3.7/site-packages/tqdm/auto.py:22: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", " from .autonotebook import tqdm as notebook_tqdm\n", "\u001b[32m[2022-11-21 02:38:07,127] [ INFO]\u001b[0m - Downloading model_config.json from https://bj.bcebos.com/paddlenlp/models/community/cross-encoder/stsb-TinyBERT-L-4/model_config.json\u001b[0m\n", "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 432/432 [00:00<00:00, 425kB/s]\n", "\u001b[32m[2022-11-21 02:38:07,197] [ INFO]\u001b[0m - We are using to load 'cross-encoder/stsb-TinyBERT-L-4'.\u001b[0m\n", "\u001b[32m[2022-11-21 02:38:07,198] [ INFO]\u001b[0m - Downloading https://bj.bcebos.com/paddlenlp/models/community/cross-encoder/stsb-TinyBERT-L-4/model_state.pdparams and saved to /root/.paddlenlp/models/cross-encoder/stsb-TinyBERT-L-4\u001b[0m\n", "\u001b[32m[2022-11-21 02:38:07,198] [ INFO]\u001b[0m - Downloading model_state.pdparams from https://bj.bcebos.com/paddlenlp/models/community/cross-encoder/stsb-TinyBERT-L-4/model_state.pdparams\u001b[0m\n", "100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 54.8M/54.8M [00:00<00:00, 64.7MB/s]\n", "\u001b[32m[2022-11-21 02:38:08,199] [ INFO]\u001b[0m - Already cached /root/.paddlenlp/models/cross-encoder/stsb-TinyBERT-L-4/model_config.json\u001b[0m\n", "W1121 02:38:08.202270 64563 gpu_resources.cc:61] Please NOTE: device: 0, GPU Compute Capability: 7.0, Driver API Version: 10.2, Runtime API Version: 10.2\n", "W1121 02:38:08.207437 64563 gpu_resources.cc:91] device: 0, cuDNN Version: 7.6.\n", "\u001b[32m[2022-11-21 02:38:09,661] [ INFO]\u001b[0m - Weights from pretrained model not used in BertModel: ['classifier.weight', 'classifier.bias']\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "(Tensor(shape=[1, 20, 312], dtype=float32, 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0.05896470]]))\n" ] } ], "source": [ "import paddle\n", "from paddlenlp.transformers import BertForSequenceClassification\n", "\n", "model = BertForSequenceClassification.from_pretrained(\"cross-encoder/stsb-TinyBERT-L-4\")\n", "input_ids = paddle.randint(100, 200, shape=[1, 20])\n", "print(model(input_ids))" ] }, { "cell_type": "markdown", "id": "aeccdfe1", "metadata": {}, "source": [ "> 此模型介绍及权重来源于[https://huggingface.co/cross-encoder/stsb-TinyBERT-L-4](https://huggingface.co/cross-encoder/stsb-TinyBERT-L-4)，并转换为飞桨模型格式。" ] } ], "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 }