SummarizationUsing_FacebookBartLargeCnn.ipynb

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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/arssite/GENAi-Assessment/blob/main/SummarizationUsing_FacebookBartLargeCnn.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install transformers torch gradio"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UQ-O25XrPhNs",
        "outputId": "ec45d6d2-618d-40ed-c4cc-d4c642f18dcc"
      },
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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            "\u001b[?25hInstalling collected packages: pydub, websockets, tomlkit, semantic-version, ruff, python-multipart, orjson, h11, ffmpy, aiofiles, uvicorn, starlette, httpcore, httpx, fastapi, gradio-client, gradio\n",
            "Successfully installed aiofiles-23.2.1 fastapi-0.115.0 ffmpy-0.4.0 gradio-4.44.1 gradio-client-1.3.0 h11-0.14.0 httpcore-1.0.6 httpx-0.27.2 orjson-3.10.7 pydub-0.25.1 python-multipart-0.0.12 ruff-0.6.9 semantic-version-2.10.0 starlette-0.38.6 tomlkit-0.12.0 uvicorn-0.31.0 websockets-12.0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
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          "height": 890,
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      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
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              "model.safetensors:   0%|          | 0.00/1.63G [00:00<?, ?B/s]"
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          "data": {
            "text/plain": [
              "vocab.json:   0%|          | 0.00/899k [00:00<?, ?B/s]"
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            "text/plain": [
              "tokenizer.json:   0%|          | 0.00/1.36M [00:00<?, ?B/s]"
            ],
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          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/tokenization_utils_base.py:1601: FutureWarning: `clean_up_tokenization_spaces` was not set. It will be set to `True` by default. This behavior will be depracted in transformers v4.45, and will be then set to `False` by default. For more details check this issue: https://github.com/huggingface/transformers/issues/31884\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Closing server running on port: 7860\n",
            "Setting queue=True in a Colab notebook requires sharing enabled. Setting `share=True` (you can turn this off by setting `share=False` in `launch()` explicitly).\n",
            "\n",
            "Colab notebook detected. To show errors in colab notebook, set debug=True in launch()\n",
            "Running on public URL: https://99c52f96efb7d9aafb.gradio.live\n",
            "\n",
            "This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "<div><iframe src=\"https://99c52f96efb7d9aafb.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": []
          },
          "metadata": {},
          "execution_count": 3
        }
      ],
      "source": [
        "import torch\n",
        "import gradio as gr\n",
        "\n",
        "from transformers import pipeline\n",
        "\n",
        "#text_summary = pipeline(\"summarization\", model=\"sshleifer/distilbart-cnn-12-6\", torch_dtype=torch.bfloat16)\n",
        "text_summary = pipeline(\"summarization\", model=\"facebook/bart-large-cnn\", torch_dtype=torch.bfloat16)\n",
        "\n",
        "\n",
        "\n",
        "def summary (input):\n",
        "    output = text_summary(input)\n",
        "    return output[0]['summary_text']\n",
        "\n",
        "gr.close_all()\n",
        "\n",
        "demo = gr.Interface(fn=summary,\n",
        "                    inputs=[gr.Textbox(label=\"Input text to summarize\",lines=6)],\n",
        "                    outputs=[gr.Textbox(label=\"Summarized text\",lines=4)],\n",
        "                    title=\"Text Summarizer Using Bart\",\n",
        "                    description=\"THIS APPLICATION WILL BE USED TO SUMMARIZE THE TEXT\")\n",
        "demo.launch()"
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "8iQ1lF80SCrA"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}