machine-learning/nlp/text-paraphrasing/Paraphrasing_with_Transformers_PythonCode.ipynb

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      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pzM7aw7wwXX3",
        "outputId": "f51a6e74-ac21-40fd-fe0f-f31141bc2243"
      },
      "outputs": [],
      "source": [
        "# !pip install transformers sentencepiece"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ISeIFTv3wbBP"
      },
      "outputs": [],
      "source": [
        "from transformers import *"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "iCFD-rjqm8Mm"
      },
      "outputs": [],
      "source": [
        "# models we gonna use for this tutorial\n",
        "model_names = [\n",
        "  \"tuner007/pegasus_paraphrase\",\n",
        "  \"Vamsi/T5_Paraphrase_Paws\",\n",
        "  \"prithivida/parrot_paraphraser_on_T5\", # Parrot\n",
        "]"
      ]
    },
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        "id": "PgrQWA_2whqN",
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      "outputs": [],
      "source": [
        "model = PegasusForConditionalGeneration.from_pretrained(\"tuner007/pegasus_paraphrase\")\n",
        "tokenizer = PegasusTokenizerFast.from_pretrained(\"tuner007/pegasus_paraphrase\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "hPtX7UCfys__"
      },
      "outputs": [],
      "source": [
        "def get_paraphrased_sentences(model, tokenizer, sentence, num_return_sequences=5, num_beams=5):\n",
        "  # tokenize the text to be form of a list of token IDs\n",
        "  inputs = tokenizer([sentence], truncation=True, padding=\"longest\", return_tensors=\"pt\")\n",
        "  # generate the paraphrased sentences\n",
        "  outputs = model.generate(\n",
        "    **inputs,\n",
        "    num_beams=num_beams,\n",
        "    num_return_sequences=num_return_sequences,\n",
        "  )\n",
        "  # decode the generated sentences using the tokenizer to get them back to text\n",
        "  return tokenizer.batch_decode(outputs, skip_special_tokens=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "9hG1HJR3Gb0Q"
      },
      "outputs": [],
      "source": [
        "sentence = \"Learning is the process of acquiring new understanding, knowledge, behaviors, skills, values, attitudes, and preferences.\""
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6P2tbSy4zdZk",
        "outputId": "517c81c8-b7f0-459a-aab7-475212f6f26d"
      },
      "outputs": [],
      "source": [
        "get_paraphrased_sentences(model, tokenizer, sentence, num_beams=10, num_return_sequences=10)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4amSI3uw7RlT",
        "outputId": "399326f7-0020-4848-dc9b-4950037351bf"
      },
      "outputs": [],
      "source": [
        "get_paraphrased_sentences(model, tokenizer, \"To paraphrase a source, you have to rewrite a passage without changing the meaning of the original text.\", num_beams=10, num_return_sequences=10)"
      ]
    },
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        "outputId": "8bb25f8e-4cb1-4521-e922-aed91c0adfce"
      },
      "outputs": [],
      "source": [
        "tokenizer = AutoTokenizer.from_pretrained(\"Vamsi/T5_Paraphrase_Paws\")\n",
        "model = AutoModelForSeq2SeqLM.from_pretrained(\"Vamsi/T5_Paraphrase_Paws\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0ONGGLOMHUtF",
        "outputId": "3769280f-a3e0-4a1a-8785-ea8ee220ad3b"
      },
      "outputs": [],
      "source": [
        "get_paraphrased_sentences(model, tokenizer, \"paraphrase: \" + \"One of the best ways to learn is to teach what you've already learned\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Wzo28toRzhGZ",
        "outputId": "dddc20d9-d326-473c-a191-7998f153c8cb"
      },
      "outputs": [],
      "source": [
        "# !pip install git+https://github.com/PrithivirajDamodaran/Parrot_Paraphraser.git"
      ]
    },
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        },
        "id": "SMFGB_iZANLt",
        "outputId": "504fcf63-5f1a-434c-91fb-49587702b1f3"
      },
      "outputs": [],
      "source": [
        "from parrot import Parrot\n",
        "\n",
        "parrot = Parrot()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "t5yWdZ_mAXp8",
        "outputId": "45bec1f4-7aaa-458d-8eb9-325296b834e8"
      },
      "outputs": [],
      "source": [
        "phrases = [\n",
        "  sentence,\n",
        "  \"One of the best ways to learn is to teach what you've already learned\",\n",
        "  \"Paraphrasing is the process of coming up with someone else's ideas in your own words\"\n",
        "]\n",
        "\n",
        "for phrase in phrases:\n",
        "  print(\"-\"*100)\n",
        "  print(\"Input_phrase: \", phrase)\n",
        "  print(\"-\"*100)\n",
        "  paraphrases = parrot.augment(input_phrase=phrase)\n",
        "  for paraphrase in paraphrases:\n",
        "   print(paraphrase)"
      ]
    }
  ],
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      "name": "Paraphrasing-with-Transformers_PythonCode.ipynb",
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