0500-huggingface-transformer-tutorial.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "H-252itL3Y2u"
   },
   "source": [
    "# 트랜스포머로 무엇을 할 수 있나요?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "vyuQn8CC_TmY"
   },
   "source": [
    "* 인프런 강의 : https://inf.run/FX4TP\n",
    "* 허깅페이스 한국어 튜토리얼 : https://huggingface.co/learn/nlp-course/ko/chapter1/1\n",
    "* colab 이나 GPU가 지원되는 환경에서 실습을 권장합니다."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "jeXafXdn3Y2y"
   },
   "source": [
    "Install the Transformers, Datasets, and Evaluate libraries to run this notebook."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "eIeica7A3Y2z",
    "outputId": "35db5dd7-bb2b-4553-aa3a-5969f741bd04"
   },
   "outputs": [],
   "source": [
    "!pip install datasets evaluate transformers[sentencepiece]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Xbi8uC9Tv9vn"
   },
   "source": [
    "## sentiment-analysis"
   ]
  },
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    },
    "id": "DnrGqmQC3Y20",
    "outputId": "703b5536-21d5-4e81-a139-4126bd965ec2"
   },
   "outputs": [],
   "source": [
    "from transformers import pipeline\n",
    "\n",
    "classifier = pipeline(\"sentiment-analysis\")\n",
    "classifier(\"I've been waiting for a HuggingFace course my whole life.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "YnmnZf8w5ZZT"
   },
   "outputs": [],
   "source": [
    "# pipeline?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "x_D-oViR3Y21",
    "outputId": "ce71d7f1-fa9f-405c-9901-b6fb08bfa44c"
   },
   "outputs": [],
   "source": [
    "classifier(\n",
    "    [\"I've been waiting for a HuggingFace course my whole life.\",\n",
    "     \"I hate this so much!\",\n",
    "     \"행복하다\",\n",
    "     \"즐겁다\",\n",
    "     \"힘들다\"]\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "pjnkkKFxtgd0"
   },
   "source": [
    "## zero-shot-classification\n",
    "* [facebook/bart-large-mnli · Hugging Face](https://huggingface.co/facebook/bart-large-mnli)"
   ]
  },
  {
   "cell_type": "code",
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    "colab": {
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    },
    "id": "O2PJEblI3Y21",
    "outputId": "ec7df811-aa1a-4fef-c56b-dfb7c8412969"
   },
   "outputs": [],
   "source": [
    "from transformers import pipeline\n",
    "\n",
    "classifier = pipeline(\"zero-shot-classification\")\n",
    "classifier(\n",
    "    \"This is a course about the Transformers library\",\n",
    "    candidate_labels=[\"education\", \"politics\", \"business\"],\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "PXGZrEd36AwM",
    "outputId": "37d3b590-592b-4bc9-ebf6-484109a67cf2"
   },
   "outputs": [],
   "source": [
    "sequence_to_classify = \"one day I will see the world\"\n",
    "candidate_labels = ['travel', 'cooking', 'dancing']\n",
    "classifier(sequence_to_classify, candidate_labels)\n",
    "#{'labels': ['travel', 'dancing', 'cooking'],\n",
    "# 'scores': [0.9938651323318481, 0.0032737774308770895, 0.002861034357920289],\n",
    "# 'sequence': 'one day I will see the world'}\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "W-hP4tkp6JFD",
    "outputId": "300e7adb-75f2-445b-facc-e605b348c9bd"
   },
   "outputs": [],
   "source": [
    "candidate_labels = ['travel', 'cooking', 'dancing', 'exploration']\n",
    "classifier(sequence_to_classify, candidate_labels, multi_label=True)\n",
    "#{'labels': ['travel', 'exploration', 'dancing', 'cooking'],\n",
    "# 'scores': [0.9945111274719238,\n",
    "#  0.9383890628814697,\n",
    "#  0.0057061901316046715,\n",
    "#  0.0018193122232332826],\n",
    "# 'sequence': 'one day I will see the world'}\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "U97tdnTBtpJ8"
   },
   "source": [
    "## text-generation\n",
    "\n",
    "* [gpt2 · Hugging Face](https://huggingface.co/gpt2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "IIhkZACP3Y22",
    "outputId": "59ab673e-762e-454a-e1db-e43c9f86a56a"
   },
   "outputs": [],
   "source": [
    "from transformers import pipeline\n",
    "\n",
    "generator = pipeline(\"text-generation\")\n",
    "generator(\"In this course, we will teach you how to\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "MauxHXQiuKtl"
   },
   "source": [
    "* [skt/kogpt2-base-v2 · Hugging Face](https://huggingface.co/skt/kogpt2-base-v2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "tN07NnxY6kXF",
    "outputId": "a203d129-37cd-4931-ddbc-f5091898e95a"
   },
   "outputs": [],
   "source": [
    "from transformers import pipeline, set_seed\n",
    "generator = pipeline('text-generation', model='skt/kogpt2-base-v2')\n",
    "set_seed(42)\n",
    "generator(\"점심 메뉴 추천,\", max_length=30, num_return_sequences=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "5ogvZLlJ3Y22",
    "outputId": "7e4c50a4-63ee-4bc7-8ea9-7f6129111a3e"
   },
   "outputs": [],
   "source": [
    "from transformers import pipeline\n",
    "\n",
    "generator = pipeline(\"text-generation\", model=\"distilgpt2\")\n",
    "generator(\n",
    "    \"In this course, we will teach you how to\",\n",
    "    max_length=30,\n",
    "    num_return_sequences=6,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "iccKrAiHuWkb"
   },
   "source": [
    "## fill-mask"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "1dNoM3T63Y23",
    "outputId": "e1f49260-a7a8-44fb-d724-7ae06180408d"
   },
   "outputs": [],
   "source": [
    "from transformers import pipeline\n",
    "\n",
    "unmasker = pipeline(\"fill-mask\")\n",
    "unmasker(\"This course will teach you all about <mask> models.\", top_k=5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "hPKz6zT_ui1H"
   },
   "source": [
    "* [klue/bert-base · Hugging Face](https://huggingface.co/klue/bert-base)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "swgCCmZf8I4Y",
    "outputId": "811a42ff-0b60-431e-d080-a0401ba29fea"
   },
   "outputs": [],
   "source": [
    "unmasker_klue = pipeline(\"fill-mask\", model=\"klue/bert-base\")\n",
    "unmasker_klue(\"한국인이 좋아하는 음식은 [MASK] 입니다.\", top_k=3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "cWhNEZ4duatu"
   },
   "source": [
    "## NER(Named Entity Recognition)\n",
    "\n",
    "* [dbmdz/bert-large-cased-finetuned-conll03-english · Hugging Face](https://huggingface.co/dbmdz/bert-large-cased-finetuned-conll03-english)"
   ]
  },
  {
   "cell_type": "code",
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    "colab": {
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    },
    "id": "Osz1_NCk3Y23",
    "outputId": "e724f261-7fe5-43f1-ed67-568473fee1b3"
   },
   "outputs": [],
   "source": [
    "from transformers import pipeline\n",
    "\n",
    "ner = pipeline(\"ner\", grouped_entities=True)\n",
    "ner(\"My name is Sylvain and I work at Hugging Face in Brooklyn.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "mR4sc3wk9j6O",
    "outputId": "440eaad6-e962-40c9-dec8-58b9dd4c6e06"
   },
   "outputs": [],
   "source": [
    "ner(\"안녕하세요. 오늘코드 유튜브 채널입니다. 여기는 대한민국입니다.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "r3Ozq_2u9qSH",
    "outputId": "668a772a-5e50-4d0b-e473-53598f2ec937"
   },
   "outputs": [],
   "source": [
    "ner(\"Hello, I'm Korean\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "LSUPSi0SwQRf"
   },
   "source": [
    "## question-answering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "0QK3PGIY3Y24",
    "outputId": "6eaf50de-aa1f-479e-ebc3-c6d325a99335"
   },
   "outputs": [],
   "source": [
    "from transformers import pipeline\n",
    "\n",
    "question_answerer = pipeline(\"question-answering\")\n",
    "question_answerer(\n",
    "    question=\"Where do I work?\",\n",
    "    context=\"My name is Sylvain and I work at todaycode in seoul\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "elNuwX6nwTrt"
   },
   "source": [
    "## summarization\n",
    "* [sshleifer/distilbart-cnn-12-6 · Hugging Face](https://huggingface.co/sshleifer/distilbart-cnn-12-6)"
   ]
  },
  {
   "cell_type": "code",
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    "id": "zJY-oE5-3Y24",
    "outputId": "9a1d3bda-1c65-42ac-acc2-db9bb496988b"
   },
   "outputs": [],
   "source": [
    "from transformers import pipeline\n",
    "\n",
    "summarizer = pipeline(\"summarization\")\n",
    "summarizer(\n",
    "    \"\"\"\n",
    "    America has changed dramatically during recent years. Not only has the number of\n",
    "    graduates in traditional engineering disciplines such as mechanical, civil,\n",
    "    electrical, chemical, and aeronautical engineering declined, but in most of\n",
    "    the premier American universities engineering curricula now concentrate on\n",
    "    and encourage largely the study of engineering science. As a result, there\n",
    "    are declining offerings in engineering subjects dealing with infrastructure,\n",
    "    the environment, and related issues, and greater concentration on high\n",
    "    technology subjects, largely supporting increasingly complex scientific\n",
    "    developments. While the latter is important, it should not be at the expense\n",
    "    of more traditional engineering.\n",
    "\n",
    "    Rapidly developing economies such as China and India, as well as other\n",
    "    industrial countries in Europe and Asia, continue to encourage and advance\n",
    "    the teaching of engineering. Both China and India, respectively, graduate\n",
    "    six and eight times as many traditional engineers as does the United States.\n",
    "    Other industrial countries at minimum maintain their output, while America\n",
    "    suffers an increasingly serious decline in the number of engineering graduates\n",
    "    and a lack of well-educated engineers.\n",
    "\"\"\"\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "JJC2TmGO1Cgw"
   },
   "source": [
    "* [gogamza/kobart-summarization · Hugging Face](https://huggingface.co/gogamza/kobart-summarization)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "y7A6tpjz_zVm",
    "outputId": "bfa40ea1-1abd-4b79-b72c-512d41aa019a"
   },
   "outputs": [],
   "source": [
    "ko_summarizer = pipeline(\"summarization\", model=\"gogamza/kobart-summarization\")\n",
    "ko_summarizer(\"상위 몇 개의 높은 확률을 띠는 토큰을 출력할지 top_k 인자를 통해 조절합니다. 여기서 모델이 특이한 <mask> 단어를 채우는 것을 주목하세요. 이를 마스크 토큰(mask token)이라고 부릅니다. 다른 마스크 채우기 모델들은 다른 형태의 마스크 토큰을 사용할 수 있기 때문에 다른 모델을 탐색할 때 항상 해당 모델의 마스크 단어가 무엇인지 확인해야 합니다. 위젯에서 사용되는 마스크 단어를 보고 이를 확인할 수 있습니다.\")"
   ]
  },
  {
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    "id": "9ZA_if5f1FlT"
   },
   "source": [
    "## translation"
   ]
  },
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    "outputId": "d8e6e7be-17b7-4bdd-a62f-98b19f4acd80"
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   "outputs": [],
   "source": [
    "from transformers import pipeline\n",
    "\n",
    "translator = pipeline(\"translation\", model=\"Helsinki-NLP/opus-mt-fr-en\")\n",
    "translator(\"Ce cours est produit par Hugging Face.\")"
   ]
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    "id": "7SBrcBDaATvm",
    "outputId": "ba1bf5c6-c810-429e-af98-187d88511091"
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   "outputs": [],
   "source": [
    "ko_translator = pipeline(\"translation\", model=\"Helsinki-NLP/opus-mt-ko-en\")\n",
    "ko_translator(\"안녕하세요.\")"
   ]
  },
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    "id": "uy_kU-fVBZ6s"
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