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        "a7f43196aef442d79b839cd78cda4137": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
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  },
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "#**Aula 2: Categorizando produtos**"
      ],
      "metadata": {
        "id": "Fh_YdbsgsVCp"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "##**Categorizando um produto**"
      ],
      "metadata": {
        "id": "bFnMuBQisY_8"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Modelo: [bart-large-mnli](https://huggingface.co/facebook/bart-large-mnli)"
      ],
      "metadata": {
        "id": "ILQbS_ppsbq4"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "pIXmqppF-26M"
      },
      "outputs": [],
      "source": [
        "from transformers import pipeline"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "classificador = pipeline('zero-shot-classification', model='facebook/bart-large-mnli')"
      ],
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        "colab": {
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        "outputId": "f2ddaa58-0e88-432f-d9f5-0f083971dff8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:89: UserWarning: \n",
            "The secret `HF_TOKEN` does not exist in your Colab secrets.\n",
            "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n",
            "You will be able to reuse this secret in all of your notebooks.\n",
            "Please note that authentication is recommended but still optional to access public models or datasets.\n",
            "  warnings.warn(\n"
          ]
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            "text/plain": [
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              "model.safetensors:   0%|          | 0.00/1.63G [00:00<?, ?B/s]"
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        {
          "output_type": "display_data",
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            "text/plain": [
              "merges.txt:   0%|          | 0.00/456k [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": [
              "tokenizer.json:   0%|          | 0.00/1.36M [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
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          },
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "categorias = ['eletronics', 'food', 'toys', 'books']"
      ],
      "metadata": {
        "id": "ZE4ICtqTCpVk"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "predicao = classificador('''\n",
        "Latest model of smartphone with 5G connectivity and 128GB internal storage''', candidate_labels=categorias)"
      ],
      "metadata": {
        "id": "FEfCfFfHDbDD"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "predicao"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2fxSp8fbD3lc",
        "outputId": "d43cdc0a-a952-42f1-b9fe-908fc0ada5cc"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'sequence': '\\nLatest model of smartphone with 5G connectivity and 128GB internal storage',\n",
              " 'labels': ['eletronics', 'food', 'books', 'toys'],\n",
              " 'scores': [0.9009801745414734,\n",
              "  0.037431977689266205,\n",
              "  0.03276699781417847,\n",
              "  0.02882087603211403]}"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##**Selecionando o modelo**"
      ],
      "metadata": {
        "id": "P3kleIivsl6d"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Modelo: [comprehend-it-multilang-base](https://huggingface.co/knowledgator/comprehend_it-multilingual-t5-base)"
      ],
      "metadata": {
        "id": "3nAoZoMZsoQh"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "pip install liqfit sentencepiece"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZihBFwEpFJxy",
        "outputId": "055bf6a5-6b29-4229-92ad-b054acbb9106"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting liqfit\n",
            "  Downloading liqfit-1.0.0-py3-none-any.whl.metadata (383 bytes)\n",
            "Requirement already satisfied: sentencepiece in /usr/local/lib/python3.10/dist-packages (0.1.99)\n",
            "Requirement already satisfied: accelerate in /usr/local/lib/python3.10/dist-packages (from liqfit) (0.32.1)\n",
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            "  Downloading kornia-0.7.3-py2.py3-none-any.whl.metadata (7.7 kB)\n",
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            "Collecting kornia-rs>=0.1.0 (from kornia->liqfit)\n",
            "  Downloading kornia_rs-0.1.5-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (8.7 kB)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from transformers->liqfit) (3.15.4)\n",
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            "Collecting nvidia-cuda-nvrtc-cu12==12.1.105 (from torch>=1.10.0->accelerate->liqfit)\n",
            "  Using cached nvidia_cuda_nvrtc_cu12-12.1.105-py3-none-manylinux1_x86_64.whl.metadata (1.5 kB)\n",
            "Collecting nvidia-cuda-runtime-cu12==12.1.105 (from torch>=1.10.0->accelerate->liqfit)\n",
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            "Collecting nvidia-cudnn-cu12==8.9.2.26 (from torch>=1.10.0->accelerate->liqfit)\n",
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            "Collecting nvidia-cufft-cu12==11.0.2.54 (from torch>=1.10.0->accelerate->liqfit)\n",
            "  Using cached nvidia_cufft_cu12-11.0.2.54-py3-none-manylinux1_x86_64.whl.metadata (1.5 kB)\n",
            "Collecting nvidia-curand-cu12==10.3.2.106 (from torch>=1.10.0->accelerate->liqfit)\n",
            "  Using cached nvidia_curand_cu12-10.3.2.106-py3-none-manylinux1_x86_64.whl.metadata (1.5 kB)\n",
            "Collecting nvidia-cusolver-cu12==11.4.5.107 (from torch>=1.10.0->accelerate->liqfit)\n",
            "  Using cached nvidia_cusolver_cu12-11.4.5.107-py3-none-manylinux1_x86_64.whl.metadata (1.6 kB)\n",
            "Collecting nvidia-cusparse-cu12==12.1.0.106 (from torch>=1.10.0->accelerate->liqfit)\n",
            "  Using cached nvidia_cusparse_cu12-12.1.0.106-py3-none-manylinux1_x86_64.whl.metadata (1.6 kB)\n",
            "Collecting nvidia-nccl-cu12==2.20.5 (from torch>=1.10.0->accelerate->liqfit)\n",
            "  Using cached nvidia_nccl_cu12-2.20.5-py3-none-manylinux2014_x86_64.whl.metadata (1.8 kB)\n",
            "Collecting nvidia-nvtx-cu12==12.1.105 (from torch>=1.10.0->accelerate->liqfit)\n",
            "  Using cached nvidia_nvtx_cu12-12.1.105-py3-none-manylinux1_x86_64.whl.metadata (1.7 kB)\n",
            "Requirement already satisfied: triton==2.3.1 in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate->liqfit) (2.3.1)\n",
            "Collecting nvidia-nvjitlink-cu12 (from nvidia-cusolver-cu12==11.4.5.107->torch>=1.10.0->accelerate->liqfit)\n",
            "  Downloading nvidia_nvjitlink_cu12-12.5.82-py3-none-manylinux2014_x86_64.whl.metadata (1.5 kB)\n",
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            "\u001b[?25hInstalling collected packages: nvidia-nvtx-cu12, nvidia-nvjitlink-cu12, nvidia-nccl-cu12, nvidia-curand-cu12, nvidia-cufft-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, kornia-rs, nvidia-cusparse-cu12, nvidia-cudnn-cu12, nvidia-cusolver-cu12, kornia, liqfit\n",
            "Successfully installed kornia-0.7.3 kornia-rs-0.1.5 liqfit-1.0.0 nvidia-cublas-cu12-12.1.3.1 nvidia-cuda-cupti-cu12-12.1.105 nvidia-cuda-nvrtc-cu12-12.1.105 nvidia-cuda-runtime-cu12-12.1.105 nvidia-cudnn-cu12-8.9.2.26 nvidia-cufft-cu12-11.0.2.54 nvidia-curand-cu12-10.3.2.106 nvidia-cusolver-cu12-11.4.5.107 nvidia-cusparse-cu12-12.1.0.106 nvidia-nccl-cu12-2.20.5 nvidia-nvjitlink-cu12-12.5.82 nvidia-nvtx-cu12-12.1.105\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from liqfit.pipeline import ZeroShotClassificationPipeline\n",
        "from liqfit.models import T5ForZeroShotClassification\n",
        "from transformers import T5Tokenizer\n",
        "\n",
        "model = T5ForZeroShotClassification.from_pretrained('knowledgator/comprehend_it-multilingual-t5-base')\n",
        "tokenizer = T5Tokenizer.from_pretrained('knowledgator/comprehend_it-multilingual-t5-base')\n",
        "classifier = ZeroShotClassificationPipeline(model=model, tokenizer=tokenizer,\n",
        "                                                      hypothesis_template = '{}', encoder_decoder = True)"
      ],
      "metadata": {
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          "height": 266,
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        "outputId": "ffdfd080-23ab-4d1d-ccfe-c7d347fa1185"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "config.json:   0%|          | 0.00/1.23k [00:00<?, ?B/s]"
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          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "You are using a model of type T5 to instantiate a model of type t5. This is not supported for all configurations of models and can yield errors.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
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          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "You are using the default legacy behaviour of the <class 'transformers.models.t5.tokenization_t5.T5Tokenizer'>. This is expected, and simply means that the `legacy` (previous) behavior will be used so nothing changes for you. If you want to use the new behaviour, set `legacy=False`. This should only be set if you understand what it means, and thoroughly read the reason why this was added as explained in https://github.com/huggingface/transformers/pull/24565\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "descricao = '''Este water gel leve e refrescante, proporciona hidratação imediata que ajuda a aliviar o\n",
        "repuxamento e aspereza da pele sensível'''\n",
        "categorias_candidatas = ['beleza', 'cozinha', 'livros']\n",
        "resultado = classifier(descricao, categorias_candidatas, multi_label=False)\n",
        "resultado"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fLYenqh1HIfW",
        "outputId": "8f019eca-924e-4d6f-c6ed-57dad1085e33"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Asking to truncate to max_length but no maximum length is provided and the model has no predefined maximum length. Default to no truncation.\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'sequence': 'Este water gel leve e refrescante, proporciona hidratação imediata que ajuda a aliviar o\\nrepuxamento e aspereza da pele sensível',\n",
              " 'labels': ['beleza', 'livros', 'cozinha'],\n",
              " 'scores': [0.9420967698097229, 0.038734421133995056, 0.019168809056282043]}"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd"
      ],
      "metadata": {
        "id": "PUI00QolHjo4"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "resultado = pd.DataFrame(resultado).drop(['sequence'], axis=1)\n",
        "resultado"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "VQMyqz3SHMLX",
        "outputId": "9a80df00-aa2c-4c0e-df01-f9ce9a4efd47"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    labels    scores\n",
              "0   beleza  0.942097\n",
              "1   livros  0.038734\n",
              "2  cozinha  0.019169"
            ],
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              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-59370964-e49c-4a7e-9170-facf7b40f85d button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_e0572e05-0bf2-43e9-bc3d-b87e3c792a96\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('resultado')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_e0572e05-0bf2-43e9-bc3d-b87e3c792a96 button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('resultado');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "resultado",
              "summary": "{\n  \"name\": \"resultado\",\n  \"rows\": 3,\n  \"fields\": [\n    {\n      \"column\": \"labels\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"beleza\",\n          \"livros\",\n          \"cozinha\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"scores\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.5272953579227693,\n        \"min\": 0.019168809056282043,\n        \"max\": 0.9420967698097229,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          0.9420967698097229,\n          0.038734421133995056,\n          0.019168809056282043\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "descricao = '''\n",
        "A fritadeira eletrica sem óleo start fry da elgin possui um design unico, capacidade para até 3,5 litros,\n",
        "potência de 1400w e revestimento antiaderente. Seu sistema de circulação de ar ultrarapido frita e economiza\n",
        "energia. Sua grelha de fritura é removivel e super fácil de limpar. Ela conta com uma proteção contra\n",
        "super aquecimento. Possui controle de temperatura de 80°c a 200°c que permite você programar a temperatura\n",
        "de preparo para cada tipo de alimento,timer para até 60 minutos com aviso sonoro e desligamento automático,\n",
        "assim você pode deixar preparando sua refeição enquanto realiza outras tarefas.\n",
        "'''\n",
        "categorias_candidatas = ['beleza', 'cozinha', 'livros']\n",
        "resultado = classifier(descricao, categorias_candidatas, multi_label=False)\n",
        "resultado = pd.DataFrame(resultado).drop(['sequence'], axis=1)\n",
        "resultado"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "Kmjz1eybHmaP",
        "outputId": "d108fc35-a9af-4a95-c2b0-12b36cea133d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    labels    scores\n",
              "0  cozinha  0.718628\n",
              "1   beleza  0.235084\n",
              "2   livros  0.046288"
            ],
            "text/html": [
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              "      <th>scores</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>cozinha</td>\n",
              "      <td>0.718628</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>beleza</td>\n",
              "      <td>0.235084</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>livros</td>\n",
              "      <td>0.046288</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
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              "    <div class=\"colab-df-buttons\">\n",
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              "      fill: #174EA6;\n",
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              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
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              "\n",
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              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
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              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-bf61d5bb-40f4-4a9a-8028-b6592c49bc5d button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-bf61d5bb-40f4-4a9a-8028-b6592c49bc5d');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
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              "        docLink.innerHTML = docLinkHtml;\n",
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              "\n",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
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              "      --hover-bg-color: #E2EBFA;\n",
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              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
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              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
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              "    display: none;\n",
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              "    width: 32px;\n",
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              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
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              "\n",
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              "    background-color: var(--disabled-bg-color);\n",
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              "\n",
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              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-f7df06c4-7000-4b1d-b918-a46d33f7fa71 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_7c2449fa-69e8-4ffe-ad1f-2103d0c82920\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('resultado')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
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              "\n",
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            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "resultado",
              "summary": "{\n  \"name\": \"resultado\",\n  \"rows\": 3,\n  \"fields\": [\n    {\n      \"column\": \"labels\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"cozinha\",\n          \"beleza\",\n          \"livros\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"scores\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.34677043036263755,\n        \"min\": 0.046288006007671356,\n        \"max\": 0.7186275124549866,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          0.7186275124549866,\n          0.23508447408676147,\n          0.046288006007671356\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##**Aplicando o modelo aos dados**"
      ],
      "metadata": {
        "id": "SX88hfFHs0No"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "dados = pd.read_csv('https://raw.githubusercontent.com/alura-cursos/hugging_face/main/Dados/descricoes_produtos.csv')\n",
        "dados"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 616
        },
        "id": "RB3Eu4ADK0w8",
        "outputId": "ba3862cd-a415-49d5-9152-f951baee3cb0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "                                            Descrição\n",
              "0   Liquidificador de alta potência com jarra de v...\n",
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              "2   Máquina de café espresso com reservatório de á...\n",
              "3   Torradeira com capacidade para quatro fatias e...\n",
              "4   Panela elétrica multifuncional que cozinha, as...\n",
              "5   Smartphone com 128GB de armazenamento e câmera...\n",
              "6   Smartwatch monitoramento de passos, frequência...\n",
              "7   Notebook gamer com placa de vídeo potente e te...\n",
              "8   Smartphone com tela super retina XDR de 6,7 po...\n",
              "9   Câmera digital com zoom óptico de 20x e vídeos...\n",
              "10  Fone de ouvido sem fio com cancelamento de ruí...\n",
              "11  Carregador portátil com capacidade de 20000mAh...\n",
              "12  Creme hidratante com ácido hialurônico para to...\n",
              "13  Shampoo fortalecedor com biotina e minerais pa...\n",
              "14  Paleta de maquiagem com 24 cores, incluindo op...\n",
              "15  Perfume feminino com notas de jasmim e sândalo...\n",
              "16  Kit de barbear com creme, pós-barba e lâminas ...\n",
              "17  Sérum facial anti-idade com vitamina C e ácido...\n",
              "18  Máscara facial de argila purificante, ideal pa...\n",
              "19  Quebra-cabeça de 1000 peças com imagem de pais...\n",
              "20  Kit de ciências para crianças com experiências...\n",
              "21  Jogo de tabuleiro clássico de estratégia para ..."
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              "summary": "{\n  \"name\": \"dados\",\n  \"rows\": 22,\n  \"fields\": [\n    {\n      \"column\": \"Descri\\u00e7\\u00e3o\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 22,\n        \"samples\": [\n          \"Liquidificador de alta pot\\u00eancia com jarra de vidro e v\\u00e1rias velocidades.\",\n          \"Shampoo fortalecedor com biotina e minerais para crescimento capilar.\",\n          \"Smartphone com tela super retina XDR de 6,7 polegadas, c\\u00e2mera tripla avan\\u00e7ada com tecnologia ProRAW e desempenho incompar\\u00e1vel gra\\u00e7as ao chip A16 Bionic.\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "categorias = ['eletrodomésticos', 'eletrônicos', 'beleza', 'brinquedos']\n",
        "\n",
        "def categorizar(descricao):\n",
        "  resultado = classifier(descricao, categorias, multi_label=False)\n",
        "  categoria_max = max(zip(resultado['labels'],resultado['scores']), key=lambda x: x[1])[0]\n",
        "  return categoria_max\n",
        "\n",
        "dados['Categoria'] = dados['Descrição'].apply(categorizar)"
      ],
      "metadata": {
        "id": "iHVLKhusLScP"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "dados"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 739
        },
        "id": "1tC5XrxZM-eM",
        "outputId": "df166152-82a8-42f0-a28d-c4026a197015"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                            Descrição         Categoria\n",
              "0   Liquidificador de alta potência com jarra de v...  eletrodomésticos\n",
              "1   Forno Micro-ondas de 20 litros, com menu desco...  eletrodomésticos\n",
              "2   Máquina de café espresso com reservatório de á...  eletrodomésticos\n",
              "3   Torradeira com capacidade para quatro fatias e...  eletrodomésticos\n",
              "4   Panela elétrica multifuncional que cozinha, as...  eletrodomésticos\n",
              "5   Smartphone com 128GB de armazenamento e câmera...       eletrônicos\n",
              "6   Smartwatch monitoramento de passos, frequência...       eletrônicos\n",
              "7   Notebook gamer com placa de vídeo potente e te...       eletrônicos\n",
              "8   Smartphone com tela super retina XDR de 6,7 po...       eletrônicos\n",
              "9   Câmera digital com zoom óptico de 20x e vídeos...       eletrônicos\n",
              "10  Fone de ouvido sem fio com cancelamento de ruí...       eletrônicos\n",
              "11  Carregador portátil com capacidade de 20000mAh...       eletrônicos\n",
              "12  Creme hidratante com ácido hialurônico para to...            beleza\n",
              "13  Shampoo fortalecedor com biotina e minerais pa...            beleza\n",
              "14  Paleta de maquiagem com 24 cores, incluindo op...            beleza\n",
              "15  Perfume feminino com notas de jasmim e sândalo...            beleza\n",
              "16  Kit de barbear com creme, pós-barba e lâminas ...            beleza\n",
              "17  Sérum facial anti-idade com vitamina C e ácido...            beleza\n",
              "18  Máscara facial de argila purificante, ideal pa...            beleza\n",
              "19  Quebra-cabeça de 1000 peças com imagem de pais...        brinquedos\n",
              "20  Kit de ciências para crianças com experiências...        brinquedos\n",
              "21  Jogo de tabuleiro clássico de estratégia para ...        brinquedos"
            ],
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              "      <th>Descrição</th>\n",
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              "      <td>Liquidificador de alta potência com jarra de v...</td>\n",
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              "      <td>eletrodomésticos</td>\n",
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              "      <th>2</th>\n",
              "      <td>Máquina de café espresso com reservatório de á...</td>\n",
              "      <td>eletrodomésticos</td>\n",
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              "      <th>3</th>\n",
              "      <td>Torradeira com capacidade para quatro fatias e...</td>\n",
              "      <td>eletrodomésticos</td>\n",
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              "      <td>Panela elétrica multifuncional que cozinha, as...</td>\n",
              "      <td>eletrodomésticos</td>\n",
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              "      <td>Smartphone com 128GB de armazenamento e câmera...</td>\n",
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              "      <td>Notebook gamer com placa de vídeo potente e te...</td>\n",
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              "      <td>Smartphone com tela super retina XDR de 6,7 po...</td>\n",
              "      <td>eletrônicos</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Câmera digital com zoom óptico de 20x e vídeos...</td>\n",
              "      <td>eletrônicos</td>\n",
              "    </tr>\n",
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              "      <th>10</th>\n",
              "      <td>Fone de ouvido sem fio com cancelamento de ruí...</td>\n",
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              "      <td>Carregador portátil com capacidade de 20000mAh...</td>\n",
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              "      <th>12</th>\n",
              "      <td>Creme hidratante com ácido hialurônico para to...</td>\n",
              "      <td>beleza</td>\n",
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              "      <th>13</th>\n",
              "      <td>Shampoo fortalecedor com biotina e minerais pa...</td>\n",
              "      <td>beleza</td>\n",
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              "      <td>beleza</td>\n",
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              "      <td>Perfume feminino com notas de jasmim e sândalo...</td>\n",
              "      <td>beleza</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>Kit de barbear com creme, pós-barba e lâminas ...</td>\n",
              "      <td>beleza</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
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              "      <td>beleza</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>Máscara facial de argila purificante, ideal pa...</td>\n",
              "      <td>beleza</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>Quebra-cabeça de 1000 peças com imagem de pais...</td>\n",
              "      <td>brinquedos</td>\n",
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              "    <tr>\n",
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              "      <td>brinquedos</td>\n",
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              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>Jogo de tabuleiro clássico de estratégia para ...</td>\n",
              "      <td>brinquedos</td>\n",
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              "summary": "{\n  \"name\": \"dados\",\n  \"rows\": 22,\n  \"fields\": [\n    {\n      \"column\": \"Descri\\u00e7\\u00e3o\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 22,\n        \"samples\": [\n          \"Liquidificador de alta pot\\u00eancia com jarra de vidro e v\\u00e1rias velocidades.\",\n          \"Shampoo fortalecedor com biotina e minerais para crescimento capilar.\",\n          \"Smartphone com tela super retina XDR de 6,7 polegadas, c\\u00e2mera tripla avan\\u00e7ada com tecnologia ProRAW e desempenho incompar\\u00e1vel gra\\u00e7as ao chip A16 Bionic.\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Categoria\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"eletr\\u00f4nicos\",\n          \"brinquedos\",\n          \"eletrodom\\u00e9sticos\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    }
  ]
}