{ "cells": [ { "cell_type": "markdown", "id": "bda1db47", "metadata": {}, "source": [ "# 🤗 + 📚 dbmdz Turkish BERT model\n" ] }, { "cell_type": "markdown", "id": "ba254a15", "metadata": {}, "source": [ "In this repository the MDZ Digital Library team (dbmdz) at the Bavarian State\n", "Library open sources a cased model for Turkish 🎉\n" ] }, { "cell_type": "markdown", "id": "bf2818ba", "metadata": {}, "source": [ "# 🇹🇷 BERTurk\n" ] }, { "cell_type": "markdown", "id": "788f7baa", "metadata": {}, "source": [ "BERTurk is a community-driven cased BERT model for Turkish.\n" ] }, { "cell_type": "markdown", "id": "5e051a7d", "metadata": {}, "source": [ "Some datasets used for pretraining and evaluation are contributed from the\n", "awesome Turkish NLP community, as well as the decision for the model name: BERTurk.\n" ] }, { "cell_type": "markdown", "id": "1edbcf52", "metadata": {}, "source": [ "## Stats\n" ] }, { "cell_type": "markdown", "id": "5b7c3ff4", "metadata": {}, "source": [ "The current version of the model is trained on a filtered and sentence\n", "segmented version of the Turkish [OSCAR corpus](https://traces1.inria.fr/oscar/),\n", "a recent Wikipedia dump, various [OPUS corpora](http://opus.nlpl.eu/) and a\n", "special corpus provided by [Kemal Oflazer](http://www.andrew.cmu.edu/user/ko/).\n" ] }, { "cell_type": "markdown", "id": "9413f21a", "metadata": {}, "source": [ "The final training corpus has a size of 35GB and 44,04,976,662 tokens.\n" ] }, { "cell_type": "markdown", "id": "25593952", "metadata": {}, "source": [ "For this model we use a vocab size of 128k.\n" ] }, { "cell_type": "markdown", "id": "962cf00d", "metadata": {}, "source": [ "## Usage\n" ] }, { "cell_type": "code", "execution_count": null, "id": "d4a4e8e3", "metadata": {}, "outputs": [], "source": [ "!pip install --upgrade paddlenlp" ] }, { "cell_type": "code", "execution_count": null, "id": "7157d7da", "metadata": {}, "outputs": [], "source": [ "import paddle\n", "from paddlenlp.transformers import AutoModel\n", "\n", "model = AutoModel.from_pretrained(\"dbmdz/bert-base-turkish-128k-cased\")\n", "input_ids = paddle.randint(100, 200, shape=[1, 20])\n", "print(model(input_ids))" ] }, { "cell_type": "markdown", "id": "e47155ee", "metadata": {}, "source": [ "# Reference" ] }, { "cell_type": "markdown", "id": "081638b2", "metadata": {}, "source": [ "> 此模型介绍及权重来源于[https://huggingface.co/dbmdz/bert-base-turkish-128k-cased](https://huggingface.co/dbmdz/bert-base-turkish-128k-cased),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 }