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      "source": [
        "# Install & Import Dependencies"
      ],
      "metadata": {
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    },
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      "source": [
        "!pip install transformers "
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            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Collecting transformers\n",
            "  Downloading transformers-4.25.1-py3-none-any.whl (5.8 MB)\n",
            "\u001b[K     |████████████████████████████████| 5.8 MB 8.7 MB/s \n",
            "\u001b[?25hRequirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.8/dist-packages (from transformers) (21.3)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.8/dist-packages (from transformers) (2.23.0)\n",
            "Collecting huggingface-hub<1.0,>=0.10.0\n",
            "  Downloading huggingface_hub-0.11.1-py3-none-any.whl (182 kB)\n",
            "\u001b[K     |████████████████████████████████| 182 kB 56.6 MB/s \n",
            "\u001b[?25hRequirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.8/dist-packages (from transformers) (4.64.1)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.8/dist-packages (from transformers) (3.8.0)\n",
            "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.8/dist-packages (from transformers) (6.0)\n",
            "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.8/dist-packages (from transformers) (1.21.6)\n",
            "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.8/dist-packages (from transformers) (2022.6.2)\n",
            "Collecting tokenizers!=0.11.3,<0.14,>=0.11.1\n",
            "  Downloading tokenizers-0.13.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (7.6 MB)\n",
            "\u001b[K     |████████████████████████████████| 7.6 MB 51.6 MB/s \n",
            "\u001b[?25hRequirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.8/dist-packages (from huggingface-hub<1.0,>=0.10.0->transformers) (4.4.0)\n",
            "Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging>=20.0->transformers) (3.0.9)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.8/dist-packages (from requests->transformers) (2.10)\n",
            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.8/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/python3.8/dist-packages (from requests->transformers) (1.24.3)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.8/dist-packages (from requests->transformers) (2022.9.24)\n",
            "Installing collected packages: tokenizers, huggingface-hub, transformers\n",
            "Successfully installed huggingface-hub-0.11.1 tokenizers-0.13.2 transformers-4.25.1\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 21,
      "metadata": {
        "id": "k9s-HbAIlVBg"
      },
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      "source": [
        "import re\n",
        "import requests\n",
        "from bs4 import BeautifulSoup\n",
        "import torch\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "from transformers import AutoTokenizer, AutoModelForSequenceClassification"
      ]
    },
    {
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      "source": [
        "# Instantiate the [Model](https://huggingface.co/nlptown/bert-base-multilingual-uncased-sentiment?text=meh%2C+It%27s++good)"
      ],
      "metadata": {
        "id": "2TuXhS0qnJJb"
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        "tokenizer = AutoTokenizer.from_pretrained(\"nlptown/bert-base-multilingual-uncased-sentiment\")\n",
        "\n",
        "model = AutoModelForSequenceClassification.from_pretrained(\"nlptown/bert-base-multilingual-uncased-sentiment\")"
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          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading:   0%|          | 0.00/112 [00:00<?, ?B/s]"
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            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "e0321df777ce49c1b1d2fad0eb5f7104"
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          "metadata": {}
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              "model_id": "f70e8e35b66749ebad552cfc10b6e486"
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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Encode & Calculate Sentiment\n"
      ],
      "metadata": {
        "id": "XLoDrQ4HnaX0"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "tokens = tokenizer.encode(\"It was really good, BRAVO!\", return_tensors='pt')\n",
        "tokens"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_LUYzNCVnZZQ",
        "outputId": "46c1eb01-898e-4b6a-fe9e-845044bbb892"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "tensor([[  101, 10197, 10140, 25165, 12050,   117, 33727,   106,   102]])"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "result = model(tokens)\n",
        "result.logits"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ek3-bwvCoJUj",
        "outputId": "9af36b7c-16fa-4aec-ef66-cd71890c01e6"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "tensor([[-2.3015, -2.2911, -0.2969,  1.7386,  2.5406]],\n",
              "       grad_fn=<AddmmBackward0>)"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# rating\n",
        "int(torch.argmax(result.logits))+1"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EbQcRz9DopW2",
        "outputId": "63b4684c-ede2-4eab-a1b1-cc1669771928"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "5"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Collect Reviews"
      ],
      "metadata": {
        "id": "JF7FeC29o-T_"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# choose a random Restaurant \n",
        "r = requests.get(\"https://www.yelp.com/biz/pauls-linz\")\n",
        "soup = BeautifulSoup(r.text, 'html.parser')"
      ],
      "metadata": {
        "id": "pjEOT0RPoqLT"
      },
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# regex = re.complie('.*raw.*')\n",
        "spans = soup.find_all('span', {'class': lambda x: x and 'raw' in x})"
      ],
      "metadata": {
        "id": "OPL7IrlOpn3j"
      },
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "reviews = [span.text for span in spans[5:]]\n",
        "reviews"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-GpF97eSp73h",
        "outputId": "b5c3e569-5a50-496c-c7b3-4a0581fb957d"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['Best place for dinner in Linz. Centrally located in old town, and a great Waygu burger on the menu. They have lots of different steak options, which I have never heard complaints about. Tried the seasonal fish here and that was a big mistake. Stick to the burger, trust me!!This place is always busy so I highly recommend a reservation. This place is good for a nice dinner and also good enough to take out of town guests and colleagues.',\n",
              " 'Good food and beer selection. Nice atmosphere and view of the Dom. Very relaxing. I will return next time i am in Linz.',\n",
              " 'Very nice restaurant and bar. The location is conveniently located right by the Cathedral and you can park underground for easy access to both locations. The service was great and the waiting time was minimal. The atmosphere of the restaurant has the old style feel of living in the past. The food was great and some dishes were very unique on taste and visual appearance which was very yummy. If you are used to an American style taste do not be disappointed if the meat is not as tender. My European company told me that meat in Germany /Austria is not as tender but the steak was well seasoned and still delicious.',\n",
              " 'During my travels, \\xa0stopped in to have a burger and a beer. Both were fantastic for a hot day.',\n",
              " 'awesome food (the burgers are amazing, so are the fries, and the beer selection is truly impressive), great atmosphere and excellent service (English menu as well as English speaking waiters were great to my non-German speaking husband). \\xa0Has a very nice urban, \"big city\" flair, which can be very refreshing if you\\'re staying in little Linz for a longer period, like we did. We saw large groups of young people, but also families with kids, couples, everyone across all age ranges. Can more than recommend this place, the location next to the Dom is also great.',\n",
              " \"this place is amazing. huge selection ales and beers in general. had three tapas and they were all awesome. walk through the glass doors to get from the bar (smoking) to the restaurant (non-smoking). staff was friendly and professional. you can even take home your favorite vacuum-sealed cut of beef. you'd expect to find this place in NYC or SF but not in Linz. well-done\"]"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Load Reviews into DataFrame and Score"
      ],
      "metadata": {
        "id": "kxTbnct_Lj7Q"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.DataFrame(data=reviews, columns=['review'])\n",
        "df"
      ],
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          "base_uri": "https://localhost:8080/",
          "height": 238
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      "outputs": [
        {
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            "text/plain": [
              "                                              review\n",
              "0  Best place for dinner in Linz. Centrally locat...\n",
              "1  Good food and beer selection. Nice atmosphere ...\n",
              "2  Very nice restaurant and bar. The location is ...\n",
              "3  During my travels,  stopped in to have a burge...\n",
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              "'Best place for dinner in Linz. Centrally located in old town, and a great Waygu burger on the menu. They have lots of different steak options, which I have never heard complaints about. Tried the seasonal fish here and that was a big mistake. Stick to the burger, trust me!!This place is always busy so I highly recommend a reservation. This place is good for a nice dinner and also good enough to take out of town guests and colleagues.'"
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        "    result = model(tokens)\n",
        "    return int(torch.argmax(result.logits))+1\n",
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              "                                              review  sentiment\n",
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              "\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",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Using Pipeline"
      ],
      "metadata": {
        "id": "KvKLcPBENSv2"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from transformers import pipeline\n",
        "\n",
        "classifier = pipeline('sentiment-analysis',\n",
        "                    model='nlptown/bert-base-multilingual-uncased-sentiment')"
      ],
      "metadata": {
        "id": "KsWW4snANSWB"
      },
      "execution_count": 29,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "classifier(\n",
        "    [df.review.iloc[0], df.review.iloc[1]]\n",
        ")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EX5N-fXuM_6T",
        "outputId": "65eb4987-05ff-420d-985b-1793927d8a1a"
      },
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[{'label': '5 stars', 'score': 0.869023323059082},\n",
              " {'label': '4 stars', 'score': 0.5727699398994446}]"
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "W0jA3BpfN_RX"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}