tabular_data_llm.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "52eae029-33fb-4034-bc95-6fdfbf5d95e3",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "\n",
    "import pandas as pd\n",
    "from pandasai import SmartDataframe\n",
    "from pandasai.llm import OpenAI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "3d941672-d81a-4002-a582-18f1509e4809",
   "metadata": {},
   "outputs": [],
   "source": [
    "spreadsheet = \"openllm_leaderboard_20230904.csv\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c37316fd-289c-4ff9-906a-3ebafea7e704",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Model</th>\n",
       "      <th>Average</th>\n",
       "      <th>ARC(25-shot)</th>\n",
       "      <th>HellaSwag(10-shot)</th>\n",
       "      <th>MMLU(5-shot)</th>\n",
       "      <th>TruthfulQA(0-shot)</th>\n",
       "      <th>Parameters</th>\n",
       "      <th>URL</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>uni-tianyan/Uni-TianYan</td>\n",
       "      <td>73.81</td>\n",
       "      <td>72.1</td>\n",
       "      <td>87.4</td>\n",
       "      <td>69.9</td>\n",
       "      <td>65.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>https://huggingface.co/uni-tianyan/Uni-TianYan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>fangloveskari/ORCA_LLaMA_70B_QLoRA</td>\n",
       "      <td>73.40</td>\n",
       "      <td>72.3</td>\n",
       "      <td>87.7</td>\n",
       "      <td>70.2</td>\n",
       "      <td>63.4</td>\n",
       "      <td>100.0</td>\n",
       "      <td>https://huggingface.co/fangloveskari/ORCA_LLaM...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>garage-bAInd/Platypus2-70B-instruct</td>\n",
       "      <td>73.13</td>\n",
       "      <td>71.8</td>\n",
       "      <td>87.9</td>\n",
       "      <td>70.5</td>\n",
       "      <td>62.3</td>\n",
       "      <td>100.0</td>\n",
       "      <td>https://huggingface.co/garage-bAInd/Platypus2-...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>upstage/Llama-2-70b-instruct-v2</td>\n",
       "      <td>72.95</td>\n",
       "      <td>71.1</td>\n",
       "      <td>87.9</td>\n",
       "      <td>70.6</td>\n",
       "      <td>62.2</td>\n",
       "      <td>100.0</td>\n",
       "      <td>https://huggingface.co/upstage/Llama-2-70b-ins...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>fangloveskari/Platypus_QLoRA_LLaMA_70b</td>\n",
       "      <td>72.94</td>\n",
       "      <td>72.1</td>\n",
       "      <td>87.5</td>\n",
       "      <td>71.0</td>\n",
       "      <td>61.2</td>\n",
       "      <td>100.0</td>\n",
       "      <td>https://huggingface.co/fangloveskari/Platypus_...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    Model  ...                                                URL\n",
       "0                 uni-tianyan/Uni-TianYan  ...     https://huggingface.co/uni-tianyan/Uni-TianYan\n",
       "1      fangloveskari/ORCA_LLaMA_70B_QLoRA  ...  https://huggingface.co/fangloveskari/ORCA_LLaM...\n",
       "2     garage-bAInd/Platypus2-70B-instruct  ...  https://huggingface.co/garage-bAInd/Platypus2-...\n",
       "3         upstage/Llama-2-70b-instruct-v2  ...  https://huggingface.co/upstage/Llama-2-70b-ins...\n",
       "4  fangloveskari/Platypus_QLoRA_LLaMA_70b  ...  https://huggingface.co/fangloveskari/Platypus_...\n",
       "\n",
       "[5 rows x 8 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(spreadsheet)\n",
    "df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "b1955f7f-4ecf-4e4d-a55c-96c74b247416",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a wrapper of an LLM for PandasAI\n",
    "llm = OpenAI(api_token=os.environ[\"OPENAI_API_KEY\"], model=\"gpt-4\")\n",
    "# Then initialize a smart DF for LLM commands\n",
    "ai_df = SmartDataframe(df, config={\"llm\": llm})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "42415cd4-9d3e-457c-a197-b3507e83ff55",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'The model that performs the best on 0-shot tasks is uni-tianyan/Uni-TianYan with a score of 65.8.'"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Fire away the tough questions\n",
    "ai_df.chat(\"Which model performs the best on 0-shot tasks and what is the score?\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "500e86fd-29ad-4690-868a-a428d7f3c21c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'The best model on 0-shot tasks is uni-tianyan/Uni-TianYan with a score of 65.8. The second best model is ehartford/Samantha-1.11-70b with a score of 65.0.'"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ai_df.chat(\"Which model performs the best on 0-shot tasks and what is the score? What is the second best model?\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "d7483344-24ef-408c-a213-6de8729f32e7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ai_df.chat(\"Show the barchart of the individual task scores for the top 5 average models\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6f9eb223-0323-438a-8d8e-0fbe45f20d23",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}