{ "cells": [ { "cell_type": "markdown", "id": "7f49bb4b", "metadata": {}, "source": [ "# Model Card for DistilRoBERTa base\n" ] }, { "cell_type": "markdown", "id": "88c832ab", "metadata": {}, "source": [ "## Model Description\n" ] }, { "cell_type": "markdown", "id": "3a2333a1", "metadata": {}, "source": [ "This model is a distilled version of the RoBERTa-base model. It follows the same training procedure as DistilBERT.\n", "The code for the distillation process can be found [here](https://github.com/huggingface/transformers/tree/master/examples/distillation).\n", "This model is case-sensitive: it makes a difference between english and English.\n" ] }, { "cell_type": "markdown", "id": "9ac70255", "metadata": {}, "source": [ "The model has 6 layers, 768 dimension and 12 heads, totalizing 82M parameters (compared to 125M parameters for RoBERTa-base).\n", "On average DistilRoBERTa is twice as fast as Roberta-base.\n" ] }, { "cell_type": "markdown", "id": "a0757c23", "metadata": {}, "source": [ "We encourage users of this model card to check out the RoBERTa-base model card to learn more about usage, limitations and potential biases.\n" ] }, { "cell_type": "markdown", "id": "2865466d", "metadata": {}, "source": [ "- **Developed by:** Victor Sanh, Lysandre Debut, Julien Chaumond, Thomas Wolf (Hugging Face)\n", "- **Model type:** Transformer-based language model\n", "- **Language(s) (NLP):** English\n", "- **License:** Apache 2.0\n", "- **Related Models:** RoBERTa-base model card\n", "- [Associated Paper](https://arxiv.org/abs/1910.01108)\n" ] }, { "cell_type": "markdown", "id": "a204fad3", "metadata": {}, "source": [ "## How to use" ] }, { "cell_type": "code", "execution_count": null, "id": "b2e488ed", "metadata": {}, "outputs": [], "source": [ "!pip install --upgrade paddlenlp" ] }, { "cell_type": "code", "execution_count": null, "id": "43d7726b", "metadata": {}, "outputs": [], "source": [ "import paddle\n", "from paddlenlp.transformers import AutoModel\n", "\n", "model = AutoModel.from_pretrained(\"distilroberta-base\")\n", "input_ids = paddle.randint(100, 200, shape=[1, 20])\n", "print(model(input_ids))" ] }, { "cell_type": "markdown", "id": "e30fb0eb", "metadata": {}, "source": [ "\n", "\n", "\n", "\n", "> 此模型介绍及权重来源于[https://huggingface.co/distilroberta-base](https://huggingface.co/distilroberta-base),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 }