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{
"cells": [
{
"cell_type": "markdown",
"id": "e26838fe",
"metadata": {},
"source": [
"# 📝 Multilingual Text Summarization (French + English)\n",
"\n",
"## 📘 Context\n",
"\n",
"Text summarization is a crucial NLP task used to extract key insights from long documents. With the advancement of transformer-based architectures like BART and T5, we can now generate high-quality summaries in different languages.\n",
"\n",
"This notebook demonstrates how to perform automatic summarization in:\n",
"- 🇬🇧 **English**, using `facebook/bart-large-cnn`\n",
"- 🇫🇷 **French**, using `plguillou/t5-base-fr-sum-cnndm`\n",
"\n",
"## 🎯 Objectives\n",
"\n",
"- Load and compare language-specific summarization models\n",
"- Generate and display summaries for both English and French input texts\n",
"- Test edge cases and observe model behavior"
]
},
{
"cell_type": "markdown",
"id": "32637c47",
"metadata": {},
"source": [
"## Packages"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "682e051c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
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]
},
{
"name": "stderr",
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"text": [
"ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
"spyder 5.2.2 requires pyqt5<5.13, which is not installed.\n",
"spyder 5.2.2 requires pyqtwebengine<5.13, which is not installed.\n",
"jupyter-server 1.18.1 requires anyio<4,>=3.1.0, but you have anyio 4.9.0 which is incompatible.\n",
"conda-repo-cli 1.0.24 requires clyent==1.2.1, but you have clyent 1.2.2 which is incompatible.\n",
"conda-repo-cli 1.0.24 requires nbformat==5.4.0, but you have nbformat 5.5.0 which is incompatible.\n",
"conda-repo-cli 1.0.24 requires requests==2.28.1, but you have requests 2.32.3 which is incompatible.\n",
"botocore 1.27.28 requires urllib3<1.27,>=1.25.4, but you have urllib3 2.4.0 which is incompatible.\n"
]
}
],
"source": [
"# !pip install transformers sentencepiece\n",
"!pip install -r requirements.txt"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "b7763e5e",
"metadata": {},
"outputs": [],
"source": [
"# import loguru\n",
"\n",
"from transformers import pipeline, AutoTokenizer, AutoModelForSeq2SeqLM\n",
"import textwrap # Text wrapping and filling\n",
"\n",
"import gradio as gr\n",
"from langdetect import detect"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "80f389cd",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "base",
"language": "python",
"name": "python3"
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"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
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"file_extension": ".py",
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"name": "python",
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"pygments_lexer": "ipython3",
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