{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "id": "D1Sg0CCPc5-3"
      },
      "outputs": [],
      "source": [
        "from huggingface_hub import list_datasets\n",
        "from toolz import concat\n",
        "from toolz import groupby\n",
        "from toolz import valmap\n",
        "from toolz import frequencies"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Grab datasets with `token-classification` task"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "id": "sJzsdvsEdDvQ"
      },
      "outputs": [],
      "source": [
        "datasets = list(list_datasets(filter=\"task_categories:token-classification\"))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IUdw59ftdLc5",
        "outputId": "21714002-6571-459b-e266-4c4838865d1f"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "DatasetInfo(id='acronym_identification', author=None, sha='c3c245a18bbd57b1682b099e14460eebf154cbdf', last_modified=datetime.datetime(2023, 1, 25, 14, 18, 28, tzinfo=datetime.timezone.utc), private=False, gated=False, disabled=False, downloads=1823, likes=17, paperswithcode_id='acronym-identification', tags=['task_categories:token-classification', 'annotations_creators:expert-generated', 'language_creators:found', 'multilinguality:monolingual', 'size_categories:10K<n<100K', 'source_datasets:original', 'language:en', 'license:mit', 'acronym-identification', 'arxiv:2010.14678', 'region:us'], card_data=None, siblings=None)"
            ]
          },
          "execution_count": 4,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "datasets[0]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 19,
      "metadata": {
        "id": "RfA9LqwYdMaq"
      },
      "outputs": [],
      "source": [
        "with_language= [dataset for dataset in datasets if \"language\" in [t.split(\":\")[0] for t in dataset.tags]]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 20,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MkU8YQMSeoCP",
        "outputId": "c226628d-0912-4d15-aa97-55aa19041743"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "DatasetInfo(id='acronym_identification', author=None, sha='c3c245a18bbd57b1682b099e14460eebf154cbdf', last_modified=datetime.datetime(2023, 1, 25, 14, 18, 28, tzinfo=datetime.timezone.utc), private=False, gated=False, disabled=False, downloads=1823, likes=17, paperswithcode_id='acronym-identification', tags=['task_categories:token-classification', 'annotations_creators:expert-generated', 'language_creators:found', 'multilinguality:monolingual', 'size_categories:10K<n<100K', 'source_datasets:original', 'language:en', 'license:mit', 'acronym-identification', 'arxiv:2010.14678', 'region:us'], card_data=None, siblings=None)"
            ]
          },
          "execution_count": 20,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "with_language[0]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 23,
      "metadata": {
        "id": "_sZ3Tuvcepbh"
      },
      "outputs": [],
      "source": [
        "def get_languages(dataset):\n",
        "    tags = list(dataset.tags)\n",
        "    languages = [t for t in tags if t.split(':')[0]=='language']\n",
        "    languages = [language for language in languages if len(language.split(\":\"))==2]\n",
        "    return [t.split(\":\")[1] for t in languages] "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 24,
      "metadata": {
        "id": "gB_2HynI1PM6"
      },
      "outputs": [],
      "source": [
        "freqs = frequencies(concat(get_languages(dataset) for dataset in with_language))\n",
        "freqs = dict(sorted(freqs.items(), key=lambda x: x[1],reverse=True))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": 28,
      "metadata": {
        "id": "Fxi6GtSxfg5D"
      },
      "outputs": [],
      "source": [
        "from huggingface_hub import list_models"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 36,
      "metadata": {
        "id": "-Hl73tkGgZFQ"
      },
      "outputs": [],
      "source": [
        "from huggingface_hub import ModelFilter\n",
        "from tqdm.auto import tqdm"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 38,
      "metadata": {
        "id": "haD8WcazgWPI"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "  0%|          | 0/393 [00:00<?, ?it/s]"
          ]
        }
      ],
      "source": [
        "no_model = []\n",
        "for lang in tqdm(freqs.keys()):\n",
        "    models_for_lang_with_task_token_classification = list(\n",
        "        list_models(filter=ModelFilter(language=lang, task=\"token-classification\"))\n",
        "    )\n",
        "    models_for_lang_any_task = list(list_models(filter=ModelFilter(language=lang)))\n",
        "    if not models_for_lang_with_task_token_classification:\n",
        "        data = {\n",
        "            \"language\": lang,\n",
        "            \"datasets\": freqs[lang],\n",
        "            \"token_classification_models\": len(\n",
        "                models_for_lang_with_task_token_classification\n",
        "            ),\n",
        "            \"all_models\": len(models_for_lang_any_task),\n",
        "        }\n",
        "        no_model.append(data)"
      ]
    },
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      "execution_count": null,
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        "colab": {
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        "id": "NmgW0P1RgkAO",
        "outputId": "301f6036-e941-401f-b4e8-f8c2f1e68d6e"
      },
      "outputs": [
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          "data": {
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              "246"
            ]
          },
          "execution_count": 74,
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