Final_work_space.ipynb

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      "source": [
        "<a href=\"https://colab.research.google.com/github/MisanthropicDeity/ELC/blob/master/Final_work_space.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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        "outputId": "999b0aa7-5c10-4a98-a99d-0870e787fc17"
      },
      "source": [
        "!pip install transformers"
      ],
      "execution_count": null,
      "outputs": [
        {
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          "text": [
            "Collecting transformers\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/50/0c/7d5950fcd80b029be0a8891727ba21e0cd27692c407c51261c3c921f6da3/transformers-4.1.1-py3-none-any.whl (1.5MB)\n",
            "\u001b[K     |████████████████████████████████| 1.5MB 5.2MB/s \n",
            "\u001b[?25hRequirement already satisfied: packaging in /usr/local/lib/python3.6/dist-packages (from transformers) (20.8)\n",
            "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.6/dist-packages (from transformers) (2019.12.20)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.6/dist-packages (from transformers) (1.19.4)\n",
            "Requirement already satisfied: dataclasses; python_version < \"3.7\" in /usr/local/lib/python3.6/dist-packages (from transformers) (0.8)\n",
            "Requirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.6/dist-packages (from transformers) (4.41.1)\n",
            "Collecting tokenizers==0.9.4\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/0f/1c/e789a8b12e28be5bc1ce2156cf87cb522b379be9cadc7ad8091a4cc107c4/tokenizers-0.9.4-cp36-cp36m-manylinux2010_x86_64.whl (2.9MB)\n",
            "\u001b[K     |████████████████████████████████| 2.9MB 18.4MB/s \n",
            "\u001b[?25hCollecting sacremoses\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/7d/34/09d19aff26edcc8eb2a01bed8e98f13a1537005d31e95233fd48216eed10/sacremoses-0.0.43.tar.gz (883kB)\n",
            "\u001b[K     |████████████████████████████████| 890kB 36.9MB/s \n",
            "\u001b[?25hRequirement already satisfied: requests in /usr/local/lib/python3.6/dist-packages (from transformers) (2.23.0)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.6/dist-packages (from transformers) (3.0.12)\n",
            "Requirement already satisfied: pyparsing>=2.0.2 in /usr/local/lib/python3.6/dist-packages (from packaging->transformers) (2.4.7)\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.6/dist-packages (from sacremoses->transformers) (1.15.0)\n",
            "Requirement already satisfied: click in /usr/local/lib/python3.6/dist-packages (from sacremoses->transformers) (7.1.2)\n",
            "Requirement already satisfied: joblib in /usr/local/lib/python3.6/dist-packages (from sacremoses->transformers) (1.0.0)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.6/dist-packages (from requests->transformers) (2020.12.5)\n",
            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.6/dist-packages (from requests->transformers) (3.0.4)\n",
            "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.6/dist-packages (from requests->transformers) (1.24.3)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.6/dist-packages (from requests->transformers) (2.10)\n",
            "Building wheels for collected packages: sacremoses\n",
            "  Building wheel for sacremoses (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for sacremoses: filename=sacremoses-0.0.43-cp36-none-any.whl size=893261 sha256=1cfa91cedad128c6a1a48650518c293b8e5e6d2d6ced383f4c7315ee34679730\n",
            "  Stored in directory: /root/.cache/pip/wheels/29/3c/fd/7ce5c3f0666dab31a50123635e6fb5e19ceb42ce38d4e58f45\n",
            "Successfully built sacremoses\n",
            "Installing collected packages: tokenizers, sacremoses, transformers\n",
            "Successfully installed sacremoses-0.0.43 tokenizers-0.9.4 transformers-4.1.1\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7aOX6JRoSv8I"
      },
      "source": [
        "import torch\n",
        "import tensorflow as tf\n",
        "from transformers import AutoTokenizer, AutoModelForQuestionAnswering"
      ],
      "execution_count": null,
      "outputs": []
    },
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            "http://localhost:8080/nbextensions/google.colab/files.js": {
              "data": 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",
              "ok": true,
              "headers": [
                [
                  "content-type",
                  "application/javascript"
                ]
              ],
              "status": 200,
              "status_text": ""
            }
          },
          "base_uri": "https://localhost:8080/",
          "height": 73
        },
        "id": "skK1VG8Sgc5Z",
        "outputId": "611e1214-4e97-491c-fafe-88a74ea339c7"
      },
      "source": [
        "from google.colab import files\n",
        "uploaded = files.upload()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-03ac05ed-3c11-4a4a-b2a1-739f6b93eb17\" name=\"files[]\" multiple disabled\n",
              "        style=\"border:none\" />\n",
              "     <output id=\"result-03ac05ed-3c11-4a4a-b2a1-739f6b93eb17\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script src=\"/nbextensions/google.colab/files.js\"></script> "
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Saving faq_covidbert.csv to faq_covidbert.csv\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yEhlyFLvlRET"
      },
      "source": [
        "import pandas as pd\n",
        "df = pd.read_csv('faq_covidbert.csv')\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "L8Fgz8JFk6hd",
        "outputId": "894ffba6-5e2a-415a-aab9-fc9e28398a98"
      },
      "source": [
        "ques = df[\"question\"][2]\n",
        "sentences = df['answer'].head(5)\n",
        "text = \" ''' \"\n",
        "for a in sentences:\n",
        "    #text+='<p>'\n",
        "    text+=a\n",
        "    #text+='<\\p>'\n",
        "text += \" ''' \"\n",
        "print (ques)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Why might someone blame or avoid individuals and groups (create stigma) because of COVID-19?\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 545,
          "referenced_widgets": [
            "7069632633394e879eecc3638248fdca",
            "1bdd05bbb4724d0f8fb7f55d2f552832",
            "44ccee4029524a7bb9a4ac78fd0d21aa",
            "6fe2349deb054ca98e36b87f68f4ba78",
            "5142441747ae4018b1de63040f33357d",
            "c2a5d681c6d541f2b19747b91b8e363d",
            "7acf6138c7b343ebb173df2b8ffc13da",
            "e9b07bf656814db5a51140cdc3fadf48"
          ]
        },
        "id": "o-dW9XDqUYR8",
        "outputId": "0da24032-37a4-4a81-c715-f87d17a8e213"
      },
      "source": [
        "tokenizer = AutoTokenizer.from_pretrained(\"https://github.com/MisanthropicDeity/ELC/blob/master/config.json\")\n",
        "model = AutoModelForQuestionAnswering.from_pretrained(\"https://github.com/MisanthropicDeity/ELC/blob/master/config.json\")\n",
        "text1 =''' Symptoms of COVID-19 are variable, ranging from mild symptoms to severe illness.[22][23] Common symptoms include fever, cough, fatigue, breathing difficulties, and loss of smell and taste. People with the same infection may have different symptoms, and their symptoms may change over time. For example, one person may have a high fever, a cough, and fatigue, and another person may have a low fever at the start of the disease and develop difficulty breathing a week later. However, in people without prior ears, nose, and throat (ENT) disorders, loss of taste combined with loss of smell is associated with COVID-19 with a specificity of 95%.[24]\n",
        "\n",
        "As is common with infections, there is a delay, known as the incubation period, between the moment a person first becomes infected and the appearance of the first symptoms. The median incubation period for COVID-19 is four to five days.[25] Most symptomatic people experience symptoms within two to seven days after exposure, and almost all symptomatic people will experience one or more symptoms before day twelve.[25][26]\n",
        "\n",
        "Around one in five people are infected with the virus but do not develop noticeable symptoms at any point in time.[27][28][29] These asymptomatic carriers tend not to get tested, and they can spread the disease.[30][31][29] Other infected people will develop symptoms later (called pre-symptomatic) or have very mild symptoms, and can also spread the virus.[32]\n",
        " '''\n",
        "\n",
        "text = '''   A novel coronavirus is a new coronavirus that has not been previously identified. The virus causing coronavirus disease 2019 (COVID-19), is not the same as the coronaviruses that commonly circulate among humans and cause mild illness, like the common cold.\n",
        "\n",
        "A diagnosis with coronavirus 229E, NL63, OC43, or HKU1 is not the same as a COVID-19 diagnosis. Patients with COVID-19 will be evaluated and cared for differently than patients with common coronavirus diagnosis.On February 11, 2020 the World Health Organization announced an official name for the disease that is causing the 2019 novel coronavirus outbreak, first identified in Wuhan China. The new name of this disease is coronavirus disease 2019, abbreviated as COVID-19. In COVID-19, ‘CO’ stands for ‘corona,’ ‘VI’ for ‘virus,’ and ‘D’ for disease. Formerly, this disease was referred to as “2019 novel coronavirus” or “2019-nCoV”.\n",
        "\n",
        "There are many types of human coronaviruses including some that commonly cause mild upper-respiratory tract illnesses. COVID-19 is a new disease, caused be a novel (or new) coronavirus that has not previously been seen in humans. The name of this disease was selected following the World Health Organization (WHO) best practiceexternal icon for naming of new human infectious diseases.People in the U.S. may be worried or anxious about friends and relatives who are living in or visiting areas where COVID-19 is spreading. Some people are worried about the disease. Fear and anxiety can lead to social stigma, for example, towards Chinese or other Asian Americans or people who were in quarantine.\n",
        "\n",
        "Stigma is discrimination against an identifiable group of people, a place, or a nation. Stigma is associated with a lack of knowledge about how COVID-19 spreads, a need to blame someone, fears about disease and death, and gossip that spreads rumors and myths.\n",
        "\n",
        "Stigma hurts everyone by creating more fear or anger towards ordinary people instead of the disease that is causing the problem.People can fight stigma and help, not hurt, others by providing social support. Counter stigma by learning and sharing facts. Communicating the facts that viruses do not target specific racial or ethnic groups and how COVID-19 actually spreads can help stop stigma.Coronaviruses are a large family of viruses. Some cause illness in people, and others, such as canine and feline coronaviruses, only infect animals. Rarely, animal coronaviruses that infect animals have emerged to infect people and can spread between people. This is suspected to have occurred for the virus that causes COVID-19. Middle East Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS) are two other examples of coronaviruses that originated from animals and then spread to people. More information about the source and spread of COVID-19 is available on the Situation Summary: Source and Spread of the Virus.This virus was first detected in Wuhan City, Hubei Province, China. The first infections were linked to a live animal market, but the virus is now spreading from person-to-person. It’s important to note that person-to-person spread can happen on a continuum. Some viruses are highly contagious (like measles), while other viruses are less so.\n",
        "\n",
        "The virus that causes COVID-19 seems to be spreading easily and sustainably in the community (“community spread”) in some affected geographic areas. Community spread means people have been infected with the virus in an area, including some who are not sure how or where they became infected.\n",
        "\n",
        "Learn what is known about the spread of newly emerged coronaviruses.The virus that causes COVID-19 is spreading from person-to-person. Someone who is actively sick with COVID-19 can spread the illness to others. That is why CDC recommends that these patients be isolated either in the hospital or at home (depending on how sick they are) until they are better and no longer pose a risk of infecting others.\n",
        "\n",
        "How long someone is actively sick can vary so the decision on when to release someone from isolation is made on a case-by-case basis in consultation with doctors, infection prevention and control experts, and public health officials and involves considering specifics of each situation including disease severity, illness signs and symptoms, and results of laboratory testing for that patient.\n",
        "\n",
        "Current CDC guidance for when it is OK to release someone from isolation is made on a case by case basis and includes meeting all of the following requirements:\n",
        "\n",
        "The patient is free from fever without the use of fever-reducing medications.\n",
        "The patient is no longer showing symptoms, including cough.\n",
        "The patient has tested negative on at least two consecutive respiratory specimens collected at least 24 hours apart.\n",
        "Someone who has been released from isolation is not considered to pose a risk of infection to others.Quarantine means separating a person or group of people who have been exposed to a contagious disease but have not developed illness (symptoms) from others who have not been exposed, in order to prevent the possible spread of that disease. Quarantine is usually established for the incubation period of the communicable disease, which is the span of time during which people have developed illness after exposure. For COVID-19, the period of quarantine is 14 days from the last date of exposure, because 14 days is the longest incubation period seen for similar coronaviruses. Someone who has been released from COVID-19 quarantine is not considered a risk for spreading the virus to others because they have not developed illness during the incubation period.Coronaviruses are generally thought to be spread from person-to-person through respiratory droplets. Currently there is no evidence to support transmission of COVID-19 associated with food. Before preparing or eating food it is important to always wash your hands with soap and water for 20 seconds for general food safety. Throughout the day wash your hands after blowing your nose, coughing or sneezing, or going to the bathroom.\n",
        "\n",
        "It may be possible that a person can get COVID-19 by touching a surface or object that has the virus on it and then touching their own mouth, nose, or possibly their eyes, but this is not thought to be the main way the virus spreads.\n",
        "\n",
        "In general, because of poor survivability of these coronaviruses on surfaces, there is likely very low risk of spread from food products or packaging that are shipped over a period of days or weeks at ambient, refrigerated, or frozen temperatures.\n",
        "\n",
        "Learn what is known about the spread of COVID-19.It is not yet known whether weather and temperature impact the spread of COVID-19. Some other viruses, like the common cold and flu, spread more during cold weather months but that does not mean it is impossible to become sick with these viruses during other months.  At this time, it is not known whether the spread of COVID-19 will decrease when weather becomes warmer.  There is much more to learn about the transmissibility, severity, and other features associated with COVID-19 and investigations are ongoing. '''\n",
        "question = \"What are the symptoms of corona ?\"\n",
        "encoding = tokenizer(question, text1, return_tensors=\"pt\")\n",
        "input_ids = encoding[\"input_ids\"]\n",
        "\n",
        "# default is local attention everywhere\n",
        "# the forward method will automatically set global attention on question tokens\n",
        "attention_mask = encoding[\"attention_mask\"]\n",
        "\n",
        "output = model(input_ids, attention_mask=attention_mask)\n",
        "all_tokens = tokenizer.convert_ids_to_tokens(input_ids[0].tolist())\n",
        "print (type(output))\n",
        "print (output)\n",
        "answer_tokens = all_tokens[torch.argmax(output['start_logits']) :torch.argmax(output['end_logits'])+1]\n",
        "answer = tokenizer.decode(tokenizer.convert_tokens_to_ids(answer_tokens))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "7069632633394e879eecc3638248fdca",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(FloatProgress(value=1.0, bar_style='info', description='Downloading', max=1.0, style=ProgressSt…"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "error",
          "ename": "OSError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mJSONDecodeError\u001b[0m                           Traceback (most recent call last)",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/transformers/configuration_utils.py\u001b[0m in \u001b[0;36mget_config_dict\u001b[0;34m(cls, pretrained_model_name_or_path, **kwargs)\u001b[0m\n\u001b[1;32m    408\u001b[0m             \u001b[0;31m# Load config dict\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 409\u001b[0;31m             \u001b[0mconfig_dict\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcls\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_dict_from_json_file\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresolved_config_file\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    410\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/transformers/configuration_utils.py\u001b[0m in \u001b[0;36m_dict_from_json_file\u001b[0;34m(cls, json_file)\u001b[0m\n\u001b[1;32m    492\u001b[0m             \u001b[0mtext\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mreader\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 493\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mjson\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloads\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtext\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    494\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/lib/python3.6/json/__init__.py\u001b[0m in \u001b[0;36mloads\u001b[0;34m(s, encoding, cls, object_hook, parse_float, parse_int, parse_constant, object_pairs_hook, **kw)\u001b[0m\n\u001b[1;32m    353\u001b[0m             parse_constant is None and object_pairs_hook is None and not kw):\n\u001b[0;32m--> 354\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0m_default_decoder\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdecode\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ms\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    355\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mcls\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/lib/python3.6/json/decoder.py\u001b[0m in \u001b[0;36mdecode\u001b[0;34m(self, s, _w)\u001b[0m\n\u001b[1;32m    338\u001b[0m         \"\"\"\n\u001b[0;32m--> 339\u001b[0;31m         \u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mend\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mraw_decode\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ms\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0midx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0m_w\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ms\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    340\u001b[0m         \u001b[0mend\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_w\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ms\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mend\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/lib/python3.6/json/decoder.py\u001b[0m in \u001b[0;36mraw_decode\u001b[0;34m(self, s, idx)\u001b[0m\n\u001b[1;32m    356\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0mStopIteration\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 357\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mJSONDecodeError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Expecting value\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0ms\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    358\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mend\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mJSONDecodeError\u001b[0m: Expecting value: line 7 column 1 (char 6)",
            "\nDuring handling of the above exception, another exception occurred:\n",
            "\u001b[0;31mOSError\u001b[0m                                   Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-35-0e01b99a4f05>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mtokenizer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mAutoTokenizer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfrom_pretrained\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"https://github.com/MisanthropicDeity/ELC/blob/master/config.json\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mmodel\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mAutoModelForQuestionAnswering\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfrom_pretrained\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"https://github.com/MisanthropicDeity/ELC/blob/master/config.json\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m text1 =''' Symptoms of COVID-19 are variable, ranging from mild symptoms to severe illness.[22][23] Common symptoms include fever, cough, fatigue, breathing difficulties, and loss of smell and taste. People with the same infection may have different symptoms, and their symptoms may change over time. For example, one person may have a high fever, a cough, and fatigue, and another person may have a low fever at the start of the disease and develop difficulty breathing a week later. However, in people without prior ears, nose, and throat (ENT) disorders, loss of taste combined with loss of smell is associated with COVID-19 with a specificity of 95%.[24]\n\u001b[1;32m      4\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0mAs\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0mcommon\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0minfections\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mthere\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0ma\u001b[0m \u001b[0mdelay\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mknown\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mthe\u001b[0m \u001b[0mincubation\u001b[0m \u001b[0mperiod\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbetween\u001b[0m \u001b[0mthe\u001b[0m \u001b[0mmoment\u001b[0m \u001b[0ma\u001b[0m \u001b[0mperson\u001b[0m \u001b[0mfirst\u001b[0m \u001b[0mbecomes\u001b[0m \u001b[0minfected\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mthe\u001b[0m \u001b[0mappearance\u001b[0m \u001b[0mof\u001b[0m \u001b[0mthe\u001b[0m \u001b[0mfirst\u001b[0m \u001b[0msymptoms\u001b[0m\u001b[0;34m.\u001b[0m \u001b[0mThe\u001b[0m \u001b[0mmedian\u001b[0m \u001b[0mincubation\u001b[0m \u001b[0mperiod\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mCOVID\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m19\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0mfour\u001b[0m \u001b[0mto\u001b[0m \u001b[0mfive\u001b[0m \u001b[0mdays\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m25\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0mMost\u001b[0m \u001b[0msymptomatic\u001b[0m \u001b[0mpeople\u001b[0m \u001b[0mexperience\u001b[0m \u001b[0msymptoms\u001b[0m \u001b[0mwithin\u001b[0m \u001b[0mtwo\u001b[0m \u001b[0mto\u001b[0m \u001b[0mseven\u001b[0m \u001b[0mdays\u001b[0m \u001b[0mafter\u001b[0m \u001b[0mexposure\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0malmost\u001b[0m \u001b[0mall\u001b[0m \u001b[0msymptomatic\u001b[0m \u001b[0mpeople\u001b[0m \u001b[0mwill\u001b[0m \u001b[0mexperience\u001b[0m \u001b[0mone\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mmore\u001b[0m \u001b[0msymptoms\u001b[0m \u001b[0mbefore\u001b[0m \u001b[0mday\u001b[0m \u001b[0mtwelve\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m25\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m26\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/transformers/models/auto/tokenization_auto.py\u001b[0m in \u001b[0;36mfrom_pretrained\u001b[0;34m(cls, pretrained_model_name_or_path, *inputs, **kwargs)\u001b[0m\n\u001b[1;32m    343\u001b[0m         \u001b[0mconfig\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"config\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    344\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mconfig\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mPretrainedConfig\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 345\u001b[0;31m             \u001b[0mconfig\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mAutoConfig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfrom_pretrained\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpretrained_model_name_or_path\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    346\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    347\u001b[0m         \u001b[0muse_fast\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"use_fast\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/transformers/models/auto/configuration_auto.py\u001b[0m in \u001b[0;36mfrom_pretrained\u001b[0;34m(cls, pretrained_model_name_or_path, **kwargs)\u001b[0m\n\u001b[1;32m    347\u001b[0m             \u001b[0;34m{\u001b[0m\u001b[0;34m'foo'\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    348\u001b[0m         \"\"\"\n\u001b[0;32m--> 349\u001b[0;31m         \u001b[0mconfig_dict\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0m_\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mPretrainedConfig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_config_dict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpretrained_model_name_or_path\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    350\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    351\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0;34m\"model_type\"\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mconfig_dict\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/transformers/configuration_utils.py\u001b[0m in \u001b[0;36mget_config_dict\u001b[0;34m(cls, pretrained_model_name_or_path, **kwargs)\u001b[0m\n\u001b[1;32m    424\u001b[0m                 \u001b[0;34m\"Please check network or file content here: {}.\"\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mconfig_file\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mresolved_config_file\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    425\u001b[0m             )\n\u001b[0;32m--> 426\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mEnvironmentError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmsg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    427\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    428\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mresolved_config_file\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0mconfig_file\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mOSError\u001b[0m: Couldn't reach server at 'https://github.com/MisanthropicDeity/ELC/blob/master/config.json' to download configuration file or configuration file is not a valid JSON file. Please check network or file content here: /root/.cache/huggingface/transformers/3c69fb17b108bf679c556b30b8bf01238f0595da2ce8599e253737ad0f01b6cb.67755a91f7ca5d87df036593f5c7f371d2cc7f56a57ae2b28311d6e08a5dda1b."
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "Cbc9WHAYcc3b",
        "outputId": "a96c6b97-d9fb-4e00-cc71-55be4a25dd46"
      },
      "source": [
        "answer"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "' democratized NLP'"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "r9M5l0dpcAg1",
        "outputId": "c64d8cd4-86f0-4052-e876-d9a6b71f9b47"
      },
      "source": [
        "type(output['start_logits'])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "torch.Tensor"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TVOSBpOKUdbe",
        "outputId": "3b3cce17-a72e-42ff-cf57-a3d58ba2cde9"
      },
      "source": [
        "from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline\n",
        "\n",
        "model_name = \"deepset/roberta-base-squad2\"\n",
        "\n",
        "# a) Get predictions\n",
        "nlp = pipeline('question-answering', model=model_name, tokenizer=model_name, args_parser= [])\n",
        "QA_input = {\n",
        "    'question': ques,\n",
        "    'context': text,\n",
        "}\n",
        "res = nlp(QA_input,topk = 2)\n",
        "# b) Load model & tokenizer\n",
        "model = AutoModelForQuestionAnswering.from_pretrained(model_name)\n",
        "tokenizer = AutoTokenizer.from_pretrained(model_name)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Some weights of RobertaModel were not initialized from the model checkpoint at deepset/roberta-base-squad2 and are newly initialized: ['roberta.pooler.dense.weight', 'roberta.pooler.dense.bias']\n",
            "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HXaVNH-0VhwN",
        "outputId": "dcf22784-376e-4666-985f-251acad7b339"
      },
      "source": [
        "print(res)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[{'score': 0.057725850492715836, 'start': 1760, 'end': 1783, 'answer': 'a need to blame someone'}, {'score': 0.04729655757546425, 'start': 2015, 'end': 2065, 'answer': 'help, not hurt, others by providing social support'}]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "z7onJRAZVwfF"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}