{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "3a55acf6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/workspace/xls-r-300m-te'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import os\n",
    "os.getcwd()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "8491f5f9",
   "metadata": {},
   "outputs": [],
   "source": [
    "from datasets import load_dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "fed9879a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "dc35d55b7a9444128bb348a38969453f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Downloading:   0%|          | 0.00/3.92k [00:00<?, ?B/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading and preparing dataset samanantar/te to /workspace/.cache/huggingface/datasets/ai4bharat___samanantar/te/0.3.0/556308f80c011cb3c32f3de18199d7b1e4cf9ca707843c92bb0bede0e47a8bd6...\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "de6defc6eb934d87ab8a18cd4fe2a04d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Downloading:   0%|          | 0.00/4.60G [00:00<?, ?B/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "0 examples [00:00, ? examples/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dataset samanantar downloaded and prepared to /workspace/.cache/huggingface/datasets/ai4bharat___samanantar/te/0.3.0/556308f80c011cb3c32f3de18199d7b1e4cf9ca707843c92bb0bede0e47a8bd6. Subsequent calls will reuse this data.\n"
     ]
    }
   ],
   "source": [
    "dataset = load_dataset(\"ai4bharat/samanantar\", \"te\", split=\"train\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "5c478941",
   "metadata": {},
   "outputs": [],
   "source": [
    "chars_to_ignore_regex = '[,?.!\\-\\;\\:\"“%‘”�—’…–]'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "abf69ac9",
   "metadata": {},
   "outputs": [],
   "source": [
    "import re\n",
    "\n",
    "def extract_text(batch):\n",
    "  text = batch[\"tgt\"]\n",
    "  batch[\"text\"] = re.sub(chars_to_ignore_regex, \"\", text.lower())\n",
    "  return batch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "6b4d0c6c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'వర్షాలకు చేతికి వచ్చిన పంట దెబ్బతిన్నదని రైతులు వాపోతున్నారు'"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset[0]['tgt']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "710de6ce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "cc51f1d8191c4118b9281727e6ec4b63",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/4661986 [00:00<?, ?ex/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dataset = dataset.map(extract_text, remove_columns=dataset.column_names)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "bd4c05b4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a0a50384591d42489963b8990624ab95",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(HTML(value='<center>\\n<img src=https://huggingface.co/front/assets/huggingface_logo-noborder.sv…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from huggingface_hub import notebook_login\n",
    "\n",
    "notebook_login()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "791becc3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "02abddfd320f404ba7970f6208f9cc27",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Pushing dataset shards to the dataset hub:   0%|          | 0/2 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dataset.push_to_hub(f\"ai4bharat__samanantar_processed_te\", split=\"train\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2d34464c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2d8308be",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
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   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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 },
 "nbformat": 4,
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}