{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Explore Dataset: docugami/dfm-csl-large-benchmark\n",
    "\n",
    "See [README](./README.md) for more information"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "DATASET_NAME=\"Docugami/dfm-csl-large-benchmark\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
      "\u001b[0m"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c5591c50842d4a6f99800ce774776236",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(HTML(value='<center> <img\\nsrc=https://huggingface.co/front/assets/huggingface_logo-noborder.sv…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# install dependencies and get a token\n",
    "!pip install datasets huggingface_hub ipywidgets\n",
    "\n",
    "from huggingface_hub import notebook_login\n",
    "notebook_login()\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Update Dataset from Github\n",
    "Note: this requires write access to the dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--2023-05-29 19:03:22--  https://raw.githubusercontent.com/docugami/DFM-benchmarks/main/data/annotations/CSL-Large.csv\n",
      "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.111.133, 185.199.110.133, 185.199.108.133, ...\n",
      "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.111.133|:443... connected.\n",
      "HTTP request sent, awaiting response... 200 OK\n",
      "Length: 1130946 (1.1M) [text/plain]\n",
      "Saving to: ‘./temp/CSL-Large.csv.1’\n",
      "\n",
      "CSL-Large.csv.1     100%[===================>]   1.08M  5.72MB/s    in 0.2s    \n",
      "\n",
      "2023-05-29 19:03:23 (5.72 MB/s) - ‘./temp/CSL-Large.csv.1’ saved [1130946/1130946]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# download latest CSV from github\n",
    "!wget -P ./temp https://raw.githubusercontent.com/docugami/DFM-benchmarks/main/data/annotations/CSL-Large.csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading and preparing dataset csv/default to /root/.cache/huggingface/datasets/csv/default-386db05c8f0598e0/0.0.0...\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "63298c1dcbd642468f3cc580bcc80297",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Downloading data files:   0%|          | 0/1 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "4d2d9eec67e64fcba634c69f2453beaf",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Extracting data files:   0%|          | 0/1 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "69c7b2b3090a488bad506b66496105c4",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Generating train split: 0 examples [00:00, ? examples/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dataset csv downloaded and prepared to /root/.cache/huggingface/datasets/csv/default-386db05c8f0598e0/0.0.0. Subsequent calls will reuse this data.\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "0c719935d3824027b1caa3260bcbbf1e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Pushing dataset shards to the dataset hub:   0%|          | 0/1 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "fb17ac28c0044959bf19f24a8c33e2a0",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Creating parquet from Arrow format:   0%|          | 0/2 [00:00<?, ?ba/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a0cc1556120a41dfaa6fa36c07cb67c2",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Upload 1 LFS files:   0%|          | 0/1 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d24bc578be9347eba62f452e489cb568",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Downloading metadata:   0%|          | 0.00/21.0 [00:00<?, ?B/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from datasets import Dataset\n",
    "\n",
    "# Load the data from the csv\n",
    "dataset = Dataset.from_csv('./temp/CSL-Large.csv')\n",
    "\n",
    "# Push the dataset to the Hugging Face Hub\n",
    "dataset.push_to_hub(DATASET_NAME, split=\"eval\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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