{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "V6LpJnLj_kVX"
      },
      "source": [
        "# Transformers, what can they do?"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RmaCJy-c_kVd"
      },
      "source": [
        "Install the Transformers, Datasets, and Evaluate libraries to run this notebook."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "En9ZDb0l_kVg",
        "outputId": "b9520091-580e-48db-f7b6-da20db63fed4",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting datasets\n",
            "  Downloading datasets-2.14.4-py3-none-any.whl (519 kB)\n",
            "\u001b[?25l     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/519.3 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K     \u001b[91m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[90m╺\u001b[0m \u001b[32m512.0/519.3 kB\u001b[0m \u001b[31m15.8 MB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0m\r\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m519.3/519.3 kB\u001b[0m \u001b[31m12.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting evaluate\n",
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            "\u001b[?25hCollecting transformers[sentencepiece]\n",
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            "\u001b[?25hCollecting safetensors>=0.3.1 (from transformers[sentencepiece])\n",
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            "\u001b[?25hCollecting sentencepiece!=0.1.92,>=0.1.91 (from transformers[sentencepiece])\n",
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            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.1->pandas->datasets) (1.16.0)\n",
            "Installing collected packages: tokenizers, sentencepiece, safetensors, xxhash, dill, responses, multiprocess, huggingface-hub, transformers, datasets, evaluate\n",
            "Successfully installed datasets-2.14.4 dill-0.3.7 evaluate-0.4.0 huggingface-hub-0.16.4 multiprocess-0.70.15 responses-0.18.0 safetensors-0.3.2 sentencepiece-0.1.99 tokenizers-0.13.3 transformers-4.31.0 xxhash-3.3.0\n"
          ]
        }
      ],
      "source": [
        "!pip install datasets evaluate transformers[sentencepiece]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "fEgd_Apr_kVj",
        "outputId": "9bcd59e0-3b94-470f-abdf-46140766cad4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 272,
          "referenced_widgets": [
            "2b227efcb1ef4fe582e260e65724a5b1",
            "eb737d74c23647c5b274ebbb3bcb732b",
            "51b0d83b31e84100aaf2b15da3e8fdb6",
            "a4ef9e1af2ee43fbab44f8e60c9eb5c7",
            "28dbb8c817474b1aaf6ef2f3d0359a8c",
            "e6ec4d00af314d7086c9def19bcc468b",
            "461cc5b087e94f14bca802c37efc59a2",
            "a374bdfffd2640ebbded683f3250ca2c",
            "f48ef84cfe0e499195e58c1dcddcbc02",
            "2f1381b5148c429f8d53172c57c85afe",
            "f834d4d65af14756ae566c9a521268e9",
            "a88cbc92b4674c35b5fb6182390a9b6b",
            "16d47dce732944dbb1159a8b787602a7",
            "1d564f837ad24e789297954ecd0c78ff",
            "62a6312e00a54939bf695a3f7d904c4e",
            "9d9721bd71914a348efc359c35914cc5",
            "2bb1a322c7004e2ba8ed51607b3435bc",
            "daf56d2079834e30b6de74589bad9860",
            "cc4905c11ad645a4857acd6423eb70a7",
            "c5703d6bdfb24358a90ddd17d13f1588",
            "5b3ef27c847c4b619a34639e59aab498",
            "df9f31a0286b440eae2b4befe06cfc3e",
            "f6b7f359b9b641db932de4741a9ae626",
            "632a7460a75b4a6ebc9d337a023e154e",
            "71cad0099de445c9aeed12eb76483fb7",
            "aec190c4da0d4a53b2015a890971ca34",
            "2cbefcc780ca41c1b5d519bc0c6313b3",
            "d34c36f3f30946e488cdd630902bee7f",
            "d98c5a77f7b047b3a5a95eabf0afe693",
            "cedc1c5d98b94259b873ebe5b39cb8d7",
            "e186eb5e9d794172b1b2972a50875aa2",
            "16b64d8eeb124059b87a6146400ffd20",
            "f1078c9d02fb4f759ade8501fc8d69ce",
            "f239e24758a14791b82ea1c8c32c2b29",
            "54c6de94cbba4a079e472acd364322c4",
            "7a19d9982458481f90c89ba5ec94a99e",
            "588f3f5b4a3e4bd983793223491f277b",
            "7856fac2d8b54b8695f56c3d1c68fbe2",
            "773d723205ad4e819ad17deb28ec57f6",
            "52b1c3c85e4748c98b5acdacc7c6a0ec",
            "575fb72fef3446ad8a1936d5670e351c",
            "e069a3773f21406b86144522c37f5f13",
            "5eee1190ba034536ae2ff418fc213e5e",
            "bc9feef128e442edb03a20ad08b85832"
          ]
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "No model was supplied, defaulted to distilbert-base-uncased-finetuned-sst-2-english and revision af0f99b (https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english).\n",
            "Using a pipeline without specifying a model name and revision in production is not recommended.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)lve/main/config.json:   0%|          | 0.00/629 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "2b227efcb1ef4fe582e260e65724a5b1"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading model.safetensors:   0%|          | 0.00/268M [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "a88cbc92b4674c35b5fb6182390a9b6b"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)okenizer_config.json:   0%|          | 0.00/48.0 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "f6b7f359b9b641db932de4741a9ae626"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)solve/main/vocab.txt:   0%|          | 0.00/232k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "f239e24758a14791b82ea1c8c32c2b29"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda'\n",
            "Xformers is not installed correctly. If you want to use memory_efficient_attention to accelerate training use the following command to install Xformers\n",
            "pip install xformers.\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[{'label': 'POSITIVE', 'score': 0.9598049521446228}]"
            ]
          },
          "metadata": {},
          "execution_count": 2
        }
      ],
      "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": 3,
      "metadata": {
        "id": "_-dhOB-6_kVk",
        "outputId": "8d2a7c21-b569-4397-cb08-99b482628672",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[{'label': 'POSITIVE', 'score': 0.9598049521446228},\n",
              " {'label': 'NEGATIVE', 'score': 0.9994558691978455}]"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ],
      "source": [
        "classifier(\n",
        "    [\"I've been waiting for a HuggingFace course my whole life.\", \"I hate this so much!\"]\n",
        ")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "id": "c0nLZLnD_kVl",
        "outputId": "76bd82a4-b364-46ff-9887-3c983874714b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 298,
          "referenced_widgets": [
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            "3d72fd5ace92444d86858c17c9eefa1c",
            "edfcd967c90a4693a2767bc5a0394e97"
          ]
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "No model was supplied, defaulted to facebook/bart-large-mnli and revision c626438 (https://huggingface.co/facebook/bart-large-mnli).\n",
            "Using a pipeline without specifying a model name and revision in production is not recommended.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)lve/main/config.json:   0%|          | 0.00/1.15k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "a8e7b786e8af453791f619c98d0b2a83"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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              "model_id": "16b051463cec450792c5014b5f00fc82"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)okenizer_config.json:   0%|          | 0.00/26.0 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "6d8e6486b7d04ec8b327abb8317c9320"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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              "model_id": "37268110048749c1beaa3eaf508c906b"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "f073c42ae24645b78a20948e800eff40"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
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              "Downloading (…)/main/tokenizer.json:   0%|          | 0.00/1.36M [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "2fba718403c2462ba5f03499ffd89dcf"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'sequence': 'This is a course about the Transformers library',\n",
              " 'labels': ['education', 'business', 'politics'],\n",
              " 'scores': [0.8445998430252075, 0.11197364330291748, 0.04342653974890709]}"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ],
      "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": 5,
      "metadata": {
        "id": "rBI7Oc3u_kVm",
        "outputId": "5a17cbda-e13d-4e21-ff53-c9c93c8caf5a",
        "colab": {
          "base_uri": "https://localhost:8080/",
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            "9e665512805847ada0ad6270e1545ca7"
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        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "No model was supplied, defaulted to gpt2 and revision 6c0e608 (https://huggingface.co/gpt2).\n",
            "Using a pipeline without specifying a model name and revision in production is not recommended.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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              "model_id": "a22c3507a9994c258e23e99dc12123ef"
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          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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              "model_id": "6d0a3cfeefe447b6a53340fb446b8a47"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)neration_config.json:   0%|          | 0.00/124 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "0c60abdf145b414293f40a02ad196afd"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "697211bf431f4ee692746c12ed9c3ea3"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "6326d4be2b3b4367bfdb03a8d27f2703"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)/main/tokenizer.json:   0%|          | 0.00/1.36M [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "6003cbb7f7654fb58228474e6cf55999"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n",
            "/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py:1369: UserWarning: Using `max_length`'s default (50) to control the generation length. This behaviour is deprecated and will be removed from the config in v5 of Transformers -- we recommend using `max_new_tokens` to control the maximum length of the generation.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[{'generated_text': \"In this course, we will teach you how to make a list of the ingredients which will cause a different type of heart attack (for example in the case of heart attack, the person who's carrying the heart, and the person in the ambulance).\"}]"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ],
      "source": [
        "from transformers import pipeline\n",
        "\n",
        "generator = pipeline(\"text-generation\")\n",
        "generator(\"In this course, we will teach you how to\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "id": "8pf6rh-M_kVn",
        "outputId": "37814221-62ac-4c2c-fa31-d33a062e6f79",
        "colab": {
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      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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              "model_id": "d28a6dd117414420a206430efae3a725"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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              "model_id": "b48881bf169f4a8db2d53b90f0b7d2b8"
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          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
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            ],
            "application/vnd.jupyter.widget-view+json": {
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          "metadata": {}
        },
        {
          "output_type": "display_data",
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            ],
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              "model_id": "4b83c8cf648f40bcbef1dae568f0f1c1"
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          "metadata": {}
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        {
          "output_type": "display_data",
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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              "model_id": "19006cb0c77747918b053c3b3983b3ed"
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        {
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          "data": {
            "text/plain": [
              "Downloading (…)/main/tokenizer.json:   0%|          | 0.00/1.36M [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "9d165d009c664333aea020d6ccde1d63"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[{'generated_text': 'In this course, we will teach you how to navigate a set of different problems with the application framework. If you are interested in more info in this'},\n",
              " {'generated_text': 'In this course, we will teach you how to install a variety of different browsers using your phone-config-v2.6-prefeatured'}]"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ],
      "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=2,\n",
        ")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "id": "sEuAzUIF_kVo",
        "outputId": "232291f9-f4af-4e8f-c548-039d25055d9d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 429,
          "referenced_widgets": [
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            "755bb4a249e04569a12c87b88a94eb16",
            "d8a5026139e24e3bb0558aab7a07e9cb",
            "ba5b366fe8a4463eabd58b657894e965",
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            "d8c117c820164b4c9b1e9e46609fdec4",
            "6f48227c6aaf4fa490c2bf9fef77bfa2"
          ]
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "No model was supplied, defaulted to distilroberta-base and revision ec58a5b (https://huggingface.co/distilroberta-base).\n",
            "Using a pipeline without specifying a model name and revision in production is not recommended.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)lve/main/config.json:   0%|          | 0.00/480 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "64a6371041544df381df846f03938fc3"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading model.safetensors:   0%|          | 0.00/331M [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "d41a2dd8a73848ecb93b540b4b0710bb"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Some weights of the model checkpoint at distilroberta-base were not used when initializing RobertaForMaskedLM: ['roberta.pooler.dense.weight', 'roberta.pooler.dense.bias']\n",
            "- This IS expected if you are initializing RobertaForMaskedLM from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
            "- This IS NOT expected if you are initializing RobertaForMaskedLM from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)olve/main/vocab.json:   0%|          | 0.00/899k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "668cf8b06f2948e6b0d0a2f0d100ca90"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)olve/main/merges.txt:   0%|          | 0.00/456k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "7cfe3ac729d743428d7bade23a7fd408"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)/main/tokenizer.json:   0%|          | 0.00/1.36M [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "21f05a5563d54c5f955137ba5b14b305"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[{'score': 0.1961979866027832,\n",
              "  'token': 30412,\n",
              "  'token_str': ' mathematical',\n",
              "  'sequence': 'This course will teach you all about mathematical models.'},\n",
              " {'score': 0.04052741825580597,\n",
              "  'token': 38163,\n",
              "  'token_str': ' computational',\n",
              "  'sequence': 'This course will teach you all about computational models.'}]"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ],
      "source": [
        "from transformers import pipeline\n",
        "\n",
        "unmasker = pipeline(\"fill-mask\")\n",
        "unmasker(\"This course will teach you all about <mask> models.\", top_k=2)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "id": "TKZduMK8_kVq",
        "outputId": "2ec1bbae-ce56-4ce6-b9c6-36304573b41a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 558,
          "referenced_widgets": [
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            "0bf4133860a94789b0c260ce35d12004",
            "657dc90fe9b047cda3e8ba65c71f5816"
          ]
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "No model was supplied, defaulted to dbmdz/bert-large-cased-finetuned-conll03-english and revision f2482bf (https://huggingface.co/dbmdz/bert-large-cased-finetuned-conll03-english).\n",
            "Using a pipeline without specifying a model name and revision in production is not recommended.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)lve/main/config.json:   0%|          | 0.00/998 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "0e13fe74f9e145a58e26fbe5db511046"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading pytorch_model.bin:   0%|          | 0.00/1.33G [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "61e02d8fed43474a81af3eff4fd1ceb2"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Some weights of the model checkpoint at dbmdz/bert-large-cased-finetuned-conll03-english were not used when initializing BertForTokenClassification: ['bert.pooler.dense.bias', 'bert.pooler.dense.weight']\n",
            "- This IS expected if you are initializing BertForTokenClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
            "- This IS NOT expected if you are initializing BertForTokenClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)okenizer_config.json:   0%|          | 0.00/60.0 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "3c123e80d8574c51ab66f9910471a524"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)solve/main/vocab.txt:   0%|          | 0.00/213k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "d5df9b8accfd4f85bd4b601189d9a569"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/pipelines/token_classification.py:169: UserWarning: `grouped_entities` is deprecated and will be removed in version v5.0.0, defaulted to `aggregation_strategy=\"simple\"` instead.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[{'entity_group': 'PER',\n",
              "  'score': 0.9981694,\n",
              "  'word': 'Sylvain',\n",
              "  'start': 11,\n",
              "  'end': 18},\n",
              " {'entity_group': 'ORG',\n",
              "  'score': 0.9796019,\n",
              "  'word': 'Hugging Face',\n",
              "  'start': 33,\n",
              "  'end': 45},\n",
              " {'entity_group': 'LOC',\n",
              "  'score': 0.9932106,\n",
              "  'word': 'Brooklyn',\n",
              "  'start': 49,\n",
              "  'end': 57}]"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ],
      "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": 9,
      "metadata": {
        "id": "V3n1vTIK_kVs",
        "outputId": "ecdfab38-b61d-427f-8950-aebef1afa33a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 251,
          "referenced_widgets": [
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            "434955b0ac5d47f38faa77341471141d",
            "f51d38b9423c40df8c2ba3abea2afa23",
            "ba908ff2eb0d4ef3bb628cb1dc6a4221",
            "19ff7e17cdf44ecc937d92528cac8df1",
            "13cf4b9e9487415db764251648678075",
            "17d4569747d1473187b89374e606c99d",
            "de314af509584bc0bc2ef3e3dbd3a066",
            "45177cdf59ad49d290a4b03cba5d3c3d",
            "443db500ace64f7b8118c479554ab116",
            "1d55b620600f4ef29006181f4e2ed9e6",
            "780f7d790dff4213b78ac4ef6fcf04ef",
            "184ff7bcfa044a359674c5b14a43220b",
            "aef7c434b60947759880c5ccdad66492",
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            "3925f32972d4459698a0a3e1659eb256"
          ]
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "No model was supplied, defaulted to distilbert-base-cased-distilled-squad and revision 626af31 (https://huggingface.co/distilbert-base-cased-distilled-squad).\n",
            "Using a pipeline without specifying a model name and revision in production is not recommended.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)lve/main/config.json:   0%|          | 0.00/473 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "9c76da141522456da3ebae146a8712d5"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading model.safetensors:   0%|          | 0.00/261M [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "1e7ddd93282f42748d540c11c2d66f56"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)okenizer_config.json:   0%|          | 0.00/29.0 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "8c4cfa4f055146ae8e91a0aa4b76b3aa"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
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              "Downloading (…)solve/main/vocab.txt:   0%|          | 0.00/213k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "e4fb589796a4414c8254c8d05c950f12"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
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              "Downloading (…)/main/tokenizer.json:   0%|          | 0.00/436k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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              "model_id": "13cf4b9e9487415db764251648678075"
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          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'score': 0.6949767470359802, 'start': 33, 'end': 45, 'answer': 'Hugging Face'}"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ],
      "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 Hugging Face in Brooklyn\",\n",
        ")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "id": "qZGvntHp_kVu",
        "outputId": "dc1b61bd-037b-482c-c95b-c2494d1c6fea",
        "colab": {
          "base_uri": "https://localhost:8080/",
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            "36e9311d74374e69a393ff0ec1720390",
            "20c5875b4f6747648fc8a343d6783404"
          ]
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "No model was supplied, defaulted to sshleifer/distilbart-cnn-12-6 and revision a4f8f3e (https://huggingface.co/sshleifer/distilbart-cnn-12-6).\n",
            "Using a pipeline without specifying a model name and revision in production is not recommended.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
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            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
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              "Downloading pytorch_model.bin:   0%|          | 0.00/1.22G [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
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              "Downloading (…)okenizer_config.json:   0%|          | 0.00/26.0 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "b44756ae3ecc42df818d51707b5daffb"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "7822335981cb461187a7a1450daae944"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)olve/main/merges.txt:   0%|          | 0.00/456k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "d3875cce96934fe08f17a35d87bcd921"
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          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[{'summary_text': ' America has changed dramatically during recent years . The number of engineering graduates in the U.S. has declined in traditional engineering disciplines such as mechanical, civil,    electrical, chemical, and aeronautical engineering . Rapidly developing economies such as China and India continue to encourage and advance the teaching of engineering .'}]"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ],
      "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": "code",
      "execution_count": 11,
      "metadata": {
        "id": "OhmKJSXA_kVv",
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      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
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            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
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              "Downloading pytorch_model.bin:   0%|          | 0.00/301M [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)neration_config.json:   0%|          | 0.00/293 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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              "model_id": "906541840e014d15b82fc777efa1c262"
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        {
          "output_type": "display_data",
          "data": {
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        {
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          "data": {
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        {
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          "data": {
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            ],
            "application/vnd.jupyter.widget-view+json": {
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        },
        {
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          "data": {
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            ],
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        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/models/marian/tokenization_marian.py:194: UserWarning: Recommended: pip install sacremoses.\n",
            "  warnings.warn(\"Recommended: pip install sacremoses.\")\n"
          ]
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        {
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            "text/plain": [
              "[{'translation_text': 'This course is produced by Hugging Face.'}]"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ],
      "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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  ],
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