{ "cells": [ { "cell_type": "markdown", "id": "f1968bb1", "metadata": {}, "source": [ "# 🤗 + 📚 dbmdz Turkish BERT model\n" ] }, { "cell_type": "markdown", "id": "37119e6e", "metadata": {}, "source": [ "In this repository the MDZ Digital Library team (dbmdz) at the Bavarian State\n", "Library open sources an uncased model for Turkish 🎉\n" ] }, { "cell_type": "markdown", "id": "e2428d3f", "metadata": {}, "source": [ "# 🇹🇷 BERTurk\n" ] }, { "cell_type": "markdown", "id": "455a98e2", "metadata": {}, "source": [ "BERTurk is a community-driven uncased BERT model for Turkish.\n" ] }, { "cell_type": "markdown", "id": "3c7b1272", "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": "cdd8f852", "metadata": {}, "source": [ "## How to use" ] }, { "cell_type": "code", "execution_count": null, "id": "81436ade", "metadata": {}, "outputs": [], "source": [ "!pip install --upgrade paddlenlp" ] }, { "cell_type": "code", "execution_count": null, "id": "bd223538", "metadata": {}, "outputs": [], "source": [ "import paddle\n", "from paddlenlp.transformers import AutoModel\n", "\n", "model = AutoModel.from_pretrained(\"dbmdz/bert-base-turkish-uncased\")\n", "input_ids = paddle.randint(100, 200, shape=[1, 20])\n", "print(model(input_ids))" ] }, { "cell_type": "markdown", "id": "7edb6fa7", "metadata": {}, "source": [ "# Reference" ] }, { "cell_type": "markdown", "id": "95b108cb", "metadata": {}, "source": [ "\n", "\n", "> The model introduction and model weights originate from [https://huggingface.co/dbmdz/bert-base-turkish-uncased](https://huggingface.co/dbmdz/bert-base-turkish-uncased) 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 }