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        "75e77fc22d514e5db4d861eb6fc4de96": {
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            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
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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/TurkuNLP/Deep_Learning_in_LangTech_course/blob/master/exercise_prompting.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "vcsdC8SNr_ix",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "32eb6735-0da9-4d89-c745-77207fb4afa9"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.6/7.6 MB\u001b[0m \u001b[31m59.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m295.0/295.0 kB\u001b[0m \u001b[31m26.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.8/7.8 MB\u001b[0m \u001b[31m108.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.3/1.3 MB\u001b[0m \u001b[31m73.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h"
          ]
        }
      ],
      "source": [
        "!pip install -q transformers"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from transformers import pipeline\n",
        "\n",
        "p = pipeline(model=\"EleutherAI/gpt-neo-2.7B\")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 209,
          "referenced_widgets": [
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        },
        "id": "bfAojj42sDRe",
        "outputId": "d5684a12-2a77-4ef1-a6f7-7c56d3b24f6b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)lve/main/config.json:   0%|          | 0.00/1.46k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "51ed05de2357478f867f5933c5bfffc8"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading model.safetensors:   0%|          | 0.00/10.7G [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "73c2d6a762b6435b91ebf33e47cb71ec"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)okenizer_config.json:   0%|          | 0.00/200 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "e58add3973bf4a78b6f9155a3ff0778f"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)olve/main/vocab.json:   0%|          | 0.00/798k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "44b76ef8f6904a5880a404408b5c6200"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)olve/main/merges.txt:   0%|          | 0.00/456k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "12c373cb84144422b6773e98959a07af"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)cial_tokens_map.json:   0%|          | 0.00/90.0 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "1a1cd269d5e64cf4b243f08af84d011f"
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Let's try simple QA first."
      ],
      "metadata": {
        "id": "WQJLKIzWR4vQ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "qa_prompt_zero = \"\"\"\n",
        "Answer the following question.\n",
        "\n",
        "Question: What is the currency of France?\n",
        "Answer: \"\"\"\n",
        "\n",
        "qa_prompt_one = \"\"\"\n",
        "Answer the following question.\n",
        "\n",
        "Question: What is the currency of US?\n",
        "Answer: Dollar\n",
        "\n",
        "Question: What is the currency of France?\n",
        "Answer: \"\"\"\n",
        "\n",
        "\n",
        "print(\"Generated zero:\", p(qa_prompt_zero, do_sample=False, max_new_tokens=50)[0][\"generated_text\"])\n",
        "print(\"---------\")\n",
        "print(\"Generated one:\", p(qa_prompt_one, do_sample=False, max_new_tokens=50)[0][\"generated_text\"])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "50vRteAjsLED",
        "outputId": "5bc334c4-bc76-47e5-9267-6c870827711c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/generation/configuration_utils.py:362: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0.9` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n",
            "  warnings.warn(\n",
            "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n",
            "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Generated zero: \n",
            "Answer the following question.\n",
            "\n",
            "Question: What is the currency of France?\n",
            "Answer:                                                   \n",
            "---------\n",
            "Generated one: \n",
            "Answer the following question.\n",
            "\n",
            "Question: What is the currency of US?\n",
            "Answer: Dollar\n",
            "\n",
            "Question: What is the currency of France?\n",
            "Answer:  Euro\n",
            "\n",
            "Question: What is the currency of Germany?\n",
            "Answer: Euro\n",
            "\n",
            "Question: What is the currency of Italy?\n",
            "Answer: Euro\n",
            "\n",
            "Question: What is the currency of Spain?\n",
            "Answer: Euro\n",
            "\n",
            "Question:\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "qa_prompt2_zero = \"\"\"\n",
        "Answer the following question.\n",
        "\n",
        "Question: Who is the President of Finland?\n",
        "Answer: \"\"\"\n",
        "\n",
        "qa_prompt2_one = \"\"\"\n",
        "Answer the following question.\n",
        "\n",
        "Question: Who is the President of US?\n",
        "Answer: Joe Biden\n",
        "\n",
        "Question: Who is the President of Finland?\n",
        "Answer: \"\"\"\n",
        "\n",
        "print(\"Generated zero:\", p(qa_prompt2_zero, do_sample=False, max_new_tokens=50)[0][\"generated_text\"])\n",
        "print(\"---------\")\n",
        "print(\"Generated one:\", p(qa_prompt2_one, do_sample=False, max_new_tokens=50)[0][\"generated_text\"])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nGENYS29TfO2",
        "outputId": "4b609982-7ebd-4fa3-a09c-b663acf46256"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/generation/configuration_utils.py:362: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0.9` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n",
            "  warnings.warn(\n",
            "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n",
            "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Generated zero: \n",
            "Answer the following question.\n",
            "\n",
            "Question: Who is the President of Finland?\n",
            "Answer:  \n",
            "\n",
            "Question: Who is the Prime Minister of Finland?\n",
            "Answer:  \n",
            "\n",
            "Question: Who is the Minister of Finance of Finland?\n",
            "Answer:  \n",
            "\n",
            "Question: Who is the Minister of Defence of Finland?\n",
            "\n",
            "---------\n",
            "Generated one: \n",
            "Answer the following question.\n",
            "\n",
            "Question: Who is the President of US?\n",
            "Answer: Joe Biden\n",
            "\n",
            "Question: Who is the President of Finland?\n",
            "Answer: \n",
            "\n",
            "Question: Who is the President of France?\n",
            "Answer: \n",
            "\n",
            "Question: Who is the President of Germany?\n",
            "Answer: \n",
            "\n",
            "Question: Who is the President of Italy?\n",
            "Answer: \n",
            "\n",
            "Question: Who\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# let's try something else\n",
        "qa_prompt2_zero = \"The president of Finland is\"\n",
        "\n",
        "qa_prompt2_one = \"The president of US is Joe Biden. The president of Finland is\"\n",
        "\n",
        "print(\"Generated zero:\", p(qa_prompt2_zero, do_sample=False, max_new_tokens=50)[0][\"generated_text\"])\n",
        "print(\"---------\")\n",
        "print(\"Generated one:\", p(qa_prompt2_one, do_sample=False, max_new_tokens=50)[0][\"generated_text\"])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ylo0BdAaYXVN",
        "outputId": "d53e4d15-2e06-4c61-8f12-53489e76eb0f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n",
            "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Generated zero: The president of Finland is a man who has been called a “national hero” and a “national embarrassment” for his role in the country’s economic miracle.\n",
            "\n",
            "But he is also a man who has been called a “national embarrassment\n",
            "---------\n",
            "Generated one: The president of US is Joe Biden. The president of Finland is Sauli Niinistö. The president of France is François Hollande. The president of Germany is Angela Merkel. The president of Italy is Matteo Renzi. The president of Spain is Mariano Rajoy. The president of the United Kingdom is\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Let's try classification next\n",
        "  * Language identification"
      ],
      "metadata": {
        "id": "9grhPnmtTwJg"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "lang_prompt_zero = \"\"\"\n",
        "Identify the language of the given text.\n",
        "\n",
        "Text: L'intelligence artificielle est un ordinateur ou un programme informatique capable d'exécuter des fonctions qui peuvent être considérées comme intelligentes.\n",
        "Language:\"\"\"\n",
        "\n",
        "lang_prompt_few = \"\"\"\n",
        "Identify the language of the given text.\n",
        "\n",
        "Text: Artificial intelligence is a computer or computer program capable of performing functions that can be considered intelligent.\n",
        "Language: English\n",
        "\n",
        "Text: La inteligencia artificial es un ordenador o programa informático capaz de realizar funciones que pueden considerarse inteligentes.\n",
        "Language: Spanish\n",
        "\n",
        "Text: L'intelligence artificielle est un ordinateur ou un programme informatique capable d'exécuter des fonctions qui peuvent être considérées comme intelligentes.\n",
        "Language: \"\"\"\n",
        "\n",
        "print(\"Generated zero:\", p(lang_prompt_zero, do_sample=False, max_new_tokens=50)[0][\"generated_text\"])\n",
        "print(\"---------\")\n",
        "print(\"Generated one:\", p(lang_prompt_few, do_sample=False, max_new_tokens=50)[0][\"generated_text\"])\n",
        "\n",
        "# Artificial intelligence is a computer or computer program capable of performing functions that can be considered intelligent.\n",
        "# L'intelligence artificielle est un ordinateur ou un programme informatique capable d'exécuter des fonctions qui peuvent être considérées comme intelligentes.\n",
        "# La inteligencia artificial es un ordenador o programa informático capaz de realizar funciones que pueden considerarse inteligentes."
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_qBnj3jn0ujm",
        "outputId": "b30248dd-2e16-4555-e9d7-4772daaf8dd9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n",
            "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Generated zero: \n",
            "Identify the language of the given text.\n",
            "\n",
            "Text: L'intelligence artificielle est un ordinateur ou un programme informatique capable d'exécuter des fonctions qui peuvent être considérées comme intelligentes.\n",
            "Language: L'intelligence artificielle est un ordinateur ou un programme informatique capable d'exécuter des fonctions qui peuvent être considérées comme intelligentes.\n",
            "\n",
            "Identify\n",
            "---------\n",
            "Generated one: \n",
            "Identify the language of the given text.\n",
            "\n",
            "Text: Artificial intelligence is a computer or computer program capable of performing functions that can be considered intelligent.\n",
            "Language: English\n",
            "\n",
            "Text: La inteligencia artificial es un ordenador o programa informático capaz de realizar funciones que pueden considerarse inteligentes.\n",
            "Language: Spanish\n",
            "\n",
            "Text: L'intelligence artificielle est un ordinateur ou un programme informatique capable d'exécuter des fonctions qui peuvent être considérées comme intelligentes.\n",
            "Language: \n",
            "\n",
            "Text: L'intelligence artificielle est un ordinateur ou un programme informatique capable d'exécuter des fonctions qui peuvent être considérées comme intelligentes.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "lang_prompt_zero = \"L'intelligence artificielle est un ordinateur ou un programme informatique capable d'exécuter des fonctions qui peuvent être considérées comme intelligentes. This sentence is written in\"\n",
        "\n",
        "print(\"Generated zero:\", p(lang_prompt_zero, do_sample=False, max_new_tokens=50)[0][\"generated_text\"])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8-je0gCfbllV",
        "outputId": "4ef4fa5f-7e2c-4f3e-d9c4-169ecbe8790c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Generated zero: L'intelligence artificielle est un ordinateur ou un programme informatique capable d'exécuter des fonctions qui peuvent être considérées comme intelligentes. This sentence is written in French.\n",
            "\n",
            "L'intelligence artificielle est un ordinateur ou un programme informatique capable d'exécuter des fonctions qui peuvent être considérées comme intelligentes.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Notes\n",
        "* I did not experiment with the generation parameters, but there are some important parameters controlling the generation:\n",
        "* `do_sample=False` means greedy decoding, i.e. always choose a token with the highest probability as the next token\n",
        "* `multinomial sampling`: randomly selects the next token based on the probability distribution over the entire vocabulary given by the model\n",
        "  - `top_k`: sample only from K most likely next words, and redistribute the probability mass among those words only\n",
        "  - `top_p`: sample from the smallest possible set of words whose cumulative probability exceeds the probability p, and redistribute the probability mass among this set of words\n",
        "  - `temperature`: increase or decrease the confidence of a model by making the probability distribution sharper (low temperature values) or smoother (high temperature values), incorporated into the softmax function\n",
        "* More about this: [https://huggingface.co/blog/how-to-generate](https://huggingface.co/blog/how-to-generate)\n"
      ],
      "metadata": {
        "id": "HCDjMKyYiQMJ"
      }
    }
  ]
}