Zero Shot Text Classification.ipynb

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  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "# Zero Shot Text Classification\n",
        "\n",
        "Large language model a lot of things already and you really need to finetune them to do the task that you want. This is an example of zero-shot text classification for something like deciding what the sentiment of a response to a survey is."
      ],
      "metadata": {
        "id": "_U_qiK8_OMjh"
      }
    },
    {
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      "source": [
        "!pip install sentence_transformers"
      ],
      "metadata": {
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        },
        "id": "OgyUozWGPEey",
        "outputId": "79ca4825-0327-4d98-b916-f89685d5f0f0"
      },
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting sentence_transformers\n",
            "  Downloading sentence_transformers-2.7.0-py3-none-any.whl (171 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m171.5/171.5 kB\u001b[0m \u001b[31m1.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: transformers<5.0.0,>=4.34.0 in /usr/local/lib/python3.10/dist-packages (from sentence_transformers) (4.40.2)\n",
            "Requirement already satisfied: tqdm in /usr/local/lib/python3.10/dist-packages (from sentence_transformers) (4.66.4)\n",
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            "Requirement already satisfied: packaging>=20.9 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub>=0.15.1->sentence_transformers) (24.0)\n",
            "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch>=1.11.0->sentence_transformers) (1.12)\n",
            "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch>=1.11.0->sentence_transformers) (3.3)\n",
            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch>=1.11.0->sentence_transformers) (3.1.4)\n",
            "Collecting nvidia-cuda-nvrtc-cu12==12.1.105 (from torch>=1.11.0->sentence_transformers)\n",
            "  Using cached nvidia_cuda_nvrtc_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (23.7 MB)\n",
            "Collecting nvidia-cuda-runtime-cu12==12.1.105 (from torch>=1.11.0->sentence_transformers)\n",
            "  Using cached nvidia_cuda_runtime_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (823 kB)\n",
            "Collecting nvidia-cuda-cupti-cu12==12.1.105 (from torch>=1.11.0->sentence_transformers)\n",
            "  Using cached nvidia_cuda_cupti_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (14.1 MB)\n",
            "Collecting nvidia-cudnn-cu12==8.9.2.26 (from torch>=1.11.0->sentence_transformers)\n",
            "  Using cached nvidia_cudnn_cu12-8.9.2.26-py3-none-manylinux1_x86_64.whl (731.7 MB)\n",
            "Collecting nvidia-cublas-cu12==12.1.3.1 (from torch>=1.11.0->sentence_transformers)\n",
            "  Using cached nvidia_cublas_cu12-12.1.3.1-py3-none-manylinux1_x86_64.whl (410.6 MB)\n",
            "Collecting nvidia-cufft-cu12==11.0.2.54 (from torch>=1.11.0->sentence_transformers)\n",
            "  Using cached nvidia_cufft_cu12-11.0.2.54-py3-none-manylinux1_x86_64.whl (121.6 MB)\n",
            "Collecting nvidia-curand-cu12==10.3.2.106 (from torch>=1.11.0->sentence_transformers)\n",
            "  Using cached nvidia_curand_cu12-10.3.2.106-py3-none-manylinux1_x86_64.whl (56.5 MB)\n",
            "Collecting nvidia-cusolver-cu12==11.4.5.107 (from torch>=1.11.0->sentence_transformers)\n",
            "  Using cached nvidia_cusolver_cu12-11.4.5.107-py3-none-manylinux1_x86_64.whl (124.2 MB)\n",
            "Collecting nvidia-cusparse-cu12==12.1.0.106 (from torch>=1.11.0->sentence_transformers)\n",
            "  Using cached nvidia_cusparse_cu12-12.1.0.106-py3-none-manylinux1_x86_64.whl (196.0 MB)\n",
            "Collecting nvidia-nccl-cu12==2.19.3 (from torch>=1.11.0->sentence_transformers)\n",
            "  Using cached nvidia_nccl_cu12-2.19.3-py3-none-manylinux1_x86_64.whl (166.0 MB)\n",
            "Collecting nvidia-nvtx-cu12==12.1.105 (from torch>=1.11.0->sentence_transformers)\n",
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            "Requirement already satisfied: triton==2.2.0 in /usr/local/lib/python3.10/dist-packages (from torch>=1.11.0->sentence_transformers) (2.2.0)\n",
            "Collecting nvidia-nvjitlink-cu12 (from nvidia-cusolver-cu12==11.4.5.107->torch>=1.11.0->sentence_transformers)\n",
            "  Using cached nvidia_nvjitlink_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl (21.1 MB)\n",
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            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub>=0.15.1->sentence_transformers) (3.3.2)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub>=0.15.1->sentence_transformers) (3.7)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub>=0.15.1->sentence_transformers) (2.0.7)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub>=0.15.1->sentence_transformers) (2024.2.2)\n",
            "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch>=1.11.0->sentence_transformers) (1.3.0)\n",
            "Installing 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, nvidia-cusparse-cu12, nvidia-cudnn-cu12, nvidia-cusolver-cu12, sentence_transformers\n",
            "Successfully installed 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-cu12-2.19.3 nvidia-nvjitlink-cu12-12.4.127 nvidia-nvtx-cu12-12.1.105 sentence_transformers-2.7.0\n"
          ]
        }
      ]
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        },
        "id": "QxJoMi1KNrbn",
        "outputId": "09983737-22da-4538-e670-a9d8461fa430"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:88: 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"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
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            ],
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            "text/plain": [
              "config_sentence_transformers.json:   0%|          | 0.00/116 [00:00<?, ?B/s]"
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        },
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            "text/plain": [
              "README.md:   0%|          | 0.00/10.7k [00:00<?, ?B/s]"
            ],
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          "data": {
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          "output_type": "display_data",
          "data": {
            "text/plain": [
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          "metadata": {}
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        {
          "output_type": "display_data",
          "data": {
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "b62b7cb54b25441ead4e41b85c8e8229"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "e99b98ecbdf64b038e488adf308a620d"
            }
          },
          "metadata": {}
        }
      ],
      "source": [
        "import torch\n",
        "import torch.nn.functional as f\n",
        "from sentence_transformers import SentenceTransformer\n",
        "\n",
        "\n",
        "text_model = SentenceTransformer('all-MiniLM-L6-v2')"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "orig_target_classes = ['happy', 'sad', 'angry', 'disgust', 'fear']\n",
        "target_classes = [f'the text describes {emotion}' for emotion in orig_target_classes]\n",
        "target_vectors = text_model.encode(target_classes, convert_to_tensor=True)\n",
        "print(target_vectors.shape)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "C4MANPrEPvzK",
        "outputId": "6e73e9ab-f8d8-427a-f644-ab0cfac3cef9"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "torch.Size([5, 384])\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sentences = [\n",
        "    'I like blue books',\n",
        "    'I was kinda in a depression eating mood so I went to the grocery to buy some junk food.',\n",
        "    'I can\\'t believe that person just threw their trash on the floor and walked away without cleaning it up!'\n",
        "]\n",
        "sentences_vectors = text_model.encode(sentences, convert_to_tensor=True)\n",
        "print(sentences_vectors.shape)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XXWzzkQ5QjdL",
        "outputId": "f78582aa-c6c6-4a51-89d9-de1ac7092e10"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "torch.Size([3, 384])\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Perform the zero-shot classification"
      ],
      "metadata": {
        "id": "ZOuJhbDYRkiA"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "zeroshot_logits = sentences_vectors @ target_vectors.T\n",
        "print(zeroshot_logits)\n",
        "\n",
        "pred_prob = f.softmax(zeroshot_logits, dim=1)\n",
        "print(pred_prob)\n",
        "\n",
        "for text, pi in zip(sentences, pred_prob.argmax(dim=1)):\n",
        "    print(f'Text: {text}')\n",
        "    print(f'Emotion: {orig_target_classes[pi]}')\n",
        "    print()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IV3Wiv5ORY_i",
        "outputId": "d282eceb-b090-49f9-e038-c075b2d02c99"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "tensor([[0.1564, 0.0687, 0.1056, 0.0922, 0.1485],\n",
            "        [0.2238, 0.2781, 0.1367, 0.1762, 0.0183],\n",
            "        [0.0173, 0.0964, 0.0944, 0.2078, 0.0612]])\n",
            "tensor([[0.2085, 0.1910, 0.1982, 0.1955, 0.2068],\n",
            "        [0.2110, 0.2227, 0.1934, 0.2012, 0.1718],\n",
            "        [0.1846, 0.1998, 0.1994, 0.2233, 0.1929]])\n",
            "Text: I like blue books\n",
            "Emotion: happy\n",
            "\n",
            "Text: I was kinda in a depression eating mood so I went to the grocery to buy some junk food.\n",
            "Emotion: sad\n",
            "\n",
            "Text: I can't believe that person just threw their trash on the floor and walked away without cleaning it up!\n",
            "Emotion: disgust\n",
            "\n"
          ]
        }
      ]
    }
  ]
}