{ "cells": [ { "cell_type": "markdown", "id": "46b7bbb6", "metadata": {}, "source": [ "# 🤗 + 📚 dbmdz German BERT models\n", "\n", "In this repository the MDZ Digital Library team (dbmdz) at the Bavarian State\n", "Library open sources another German BERT models 🎉\n", "\n", "# German BERT\n", "\n", "## Stats\n", "\n", "In addition to the recently released [German BERT](https://deepset.ai/german-bert)\n", "model by [deepset](https://deepset.ai/) we provide another German-language model.\n", "\n", "The source data for the model consists of a recent Wikipedia dump, EU Bookshop corpus,\n", "Open Subtitles, CommonCrawl, ParaCrawl and News Crawl. This results in a dataset with\n", "a size of 16GB and 2,350,234,427 tokens.\n", "\n", "For sentence splitting, we use [spacy](https://spacy.io/). Our preprocessing steps\n", "(sentence piece model for vocab generation) follow those used for training\n", "[SciBERT](https://github.com/allenai/scibert). The model is trained with an initial\n", "sequence length of 512 subwords and was performed for 1.5M steps." ] }, { "cell_type": "markdown", "id": "bc37d3e3", "metadata": {}, "source": [ "## How to use" ] }, { "cell_type": "code", "execution_count": null, "id": "2afff18c", "metadata": {}, "outputs": [], "source": [ "!pip install --upgrade paddlenlp" ] }, { "cell_type": "code", "execution_count": null, "id": "967f058e", "metadata": {}, "outputs": [], "source": [ "import paddle\n", "from paddlenlp.transformers import AutoModel\n", "\n", "model = AutoModel.from_pretrained(\"dbmdz/bert-base-german-uncased\")\n", "input_ids = paddle.randint(100, 200, shape=[1, 20])\n", "print(model(input_ids))" ] }, { "cell_type": "markdown", "id": "483dbced", "metadata": {}, "source": [ "# Reference" ] }, { "cell_type": "markdown", "id": "04e50d8c", "metadata": {}, "source": [ "\n", "> 此模型介绍及权重来源于[https://huggingface.co/dbmdz/bert-base-german-uncased](https://huggingface.co/dbmdz/bert-base-german-uncased),并转换为飞桨模型格式。\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 }