Compiling the results together

compile-results.ipynb

@@ -0,0 +1,863 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Defaulting to user installation because normal site-packages is not writeable\n",
+      "Requirement already satisfied: pandas in /Users/picocreator/Library/Python/3.9/lib/python/site-packages (2.2.0)\n",
+      "Requirement already satisfied: tzdata>=2022.7 in /Users/picocreator/Library/Python/3.9/lib/python/site-packages (from pandas) (2024.1)\n",
+      "Requirement already satisfied: python-dateutil>=2.8.2 in /Users/picocreator/Library/Python/3.9/lib/python/site-packages (from pandas) (2.8.2)\n",
+      "Requirement already satisfied: pytz>=2020.1 in /Users/picocreator/Library/Python/3.9/lib/python/site-packages (from pandas) (2024.1)\n",
+      "Requirement already satisfied: numpy<2,>=1.22.4 in /Users/picocreator/Library/Python/3.9/lib/python/site-packages (from pandas) (1.26.1)\n",
+      "Requirement already satisfied: six>=1.5 in /Library/Developer/CommandLineTools/Library/Frameworks/Python3.framework/Versions/3.9/lib/python3.9/site-packages (from python-dateutil>=2.8.2->pandas) (1.15.0)\n",
+      "\u001b[33mWARNING: You are using pip version 21.2.4; however, version 24.0 is available.\n",
+      "You should consider upgrading via the '/Library/Developer/CommandLineTools/usr/bin/python3 -m pip install --upgrade pip' command.\u001b[0m\n"
+     ]
+    }
+   ],
+   "source": [
+    "!pip3 install pandas"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Get the filelist\n",
+    "\n",
+    "For the full results.json"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Found 2217 results.json files\n"
+     ]
+    }
+   ],
+   "source": [
+    "import glob\n",
+    "\n",
+    "# Specify the path to the folder containing the results.json files\n",
+    "folder_path = \"lm-eval-output\"\n",
+    "\n",
+    "# Use glob to find all the results.json files\n",
+    "results_json_files = glob.glob(f\"{folder_path}/**/results.json\", recursive=True)\n",
+    "\n",
+    "# Show total number of results.json files found\n",
+    "print(f\"Found {len(results_json_files)} results.json files\")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Process all the results.json\n",
+    "\n",
+    "One file at a time"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Processed example:  {'name': 'bigscience/bloom-7b1', 'config': {'dtype=bfloat16,trust_remote_code=True': {'confStr': 'dtype=bfloat16,trust_remote_code=True', 'confObj': {'dtype': 'bfloat16', 'trust_remote_code': 'True'}, 'results': {'xcopa': {'acc,none': 0.5709090909090908, 'acc_stderr,none': 0.06135942275478038, 'alias': 'xcopa'}, 'xcopa_et': {'acc,none': 0.482, 'acc_stderr,none': 0.02236856511738799, 'alias': ' - xcopa_et'}, 'xcopa_ht': {'acc,none': 0.516, 'acc_stderr,none': 0.0223716109825804, 'alias': ' - xcopa_ht'}, 'xcopa_id': {'acc,none': 0.702, 'acc_stderr,none': 0.020475118092988978, 'alias': ' - xcopa_id'}, 'xcopa_it': {'acc,none': 0.528, 'acc_stderr,none': 0.022347949832668093, 'alias': ' - xcopa_it'}, 'xcopa_qu': {'acc,none': 0.512, 'acc_stderr,none': 0.02237662679792717, 'alias': ' - xcopa_qu'}, 'xcopa_sw': {'acc,none': 0.518, 'acc_stderr,none': 0.02236856511738799, 'alias': ' - xcopa_sw'}, 'xcopa_ta': {'acc,none': 0.592, 'acc_stderr,none': 0.02200091089387719, 'alias': ' - xcopa_ta'}, 'xcopa_th': {'acc,none': 0.552, 'acc_stderr,none': 0.022261697292270132, 'alias': ' - xcopa_th'}, 'xcopa_tr': {'acc,none': 0.512, 'acc_stderr,none': 0.02237662679792717, 'alias': ' - xcopa_tr'}, 'xcopa_vi': {'acc,none': 0.716, 'acc_stderr,none': 0.02018670369357085, 'alias': ' - xcopa_vi'}, 'xcopa_zh': {'acc,none': 0.65, 'acc_stderr,none': 0.021352091786223104, 'alias': ' - xcopa_zh'}, 'xnli': {'acc,none': 0.41204819277108434, 'acc_stderr,none': 0.051535476594892576, 'alias': 'xnli'}, 'xnli_ar': {'acc,none': 0.3377510040160643, 'acc_stderr,none': 0.009479742273956477, 'alias': ' - xnli_ar'}, 'xnli_bg': {'acc,none': 0.3779116465863454, 'acc_stderr,none': 0.009718712281227459, 'alias': ' - xnli_bg'}, 'xnli_de': {'acc,none': 0.41365461847389556, 'acc_stderr,none': 0.009871502159099368, 'alias': ' - xnli_de'}, 'xnli_el': {'acc,none': 0.3650602409638554, 'acc_stderr,none': 0.009650194822749637, 'alias': ' - xnli_el'}, 'xnli_en': {'acc,none': 0.5261044176706827, 'acc_stderr,none': 0.01000840465166064, 'alias': ' - xnli_en'}, 'xnli_es': {'acc,none': 0.4879518072289157, 'acc_stderr,none': 0.010019162857624487, 'alias': ' - xnli_es'}, 'xnli_fr': {'acc,none': 0.478714859437751, 'acc_stderr,none': 0.010012987604500423, 'alias': ' - xnli_fr'}, 'xnli_hi': {'acc,none': 0.4666666666666667, 'acc_stderr,none': 0.00999977679318763, 'alias': ' - xnli_hi'}, 'xnli_ru': {'acc,none': 0.43253012048192774, 'acc_stderr,none': 0.009930409027139453, 'alias': ' - xnli_ru'}, 'xnli_sw': {'acc,none': 0.3855421686746988, 'acc_stderr,none': 0.009755949341224318, 'alias': ' - xnli_sw'}, 'xnli_th': {'acc,none': 0.3437751004016064, 'acc_stderr,none': 0.009520310502882936, 'alias': ' - xnli_th'}, 'xnli_tr': {'acc,none': 0.3522088353413655, 'acc_stderr,none': 0.009574259292495757, 'alias': ' - xnli_tr'}, 'xnli_ur': {'acc,none': 0.42289156626506025, 'acc_stderr,none': 0.009902179034797438, 'alias': ' - xnli_ur'}, 'xnli_vi': {'acc,none': 0.44497991967871486, 'acc_stderr,none': 0.009961210239024633, 'alias': ' - xnli_vi'}, 'xnli_zh': {'acc,none': 0.3449799196787149, 'acc_stderr,none': 0.009528219800053311, 'alias': ' - xnli_zh'}, 'pawsx': {'acc,none': 0.5078571428571429, 'acc_stderr,none': 0.03988534011535243, 'alias': 'pawsx'}, 'paws_de': {'acc,none': 0.5175, 'acc_stderr,none': 0.011176284251254179, 'alias': ' - paws_de'}, 'paws_en': {'acc,none': 0.4145, 'acc_stderr,none': 0.011018419931591767, 'alias': ' - paws_en'}, 'paws_es': {'acc,none': 0.437, 'acc_stderr,none': 0.011094009127418984, 'alias': ' - paws_es'}, 'paws_fr': {'acc,none': 0.5435, 'acc_stderr,none': 0.011140733053371404, 'alias': ' - paws_fr'}, 'paws_ja': {'acc,none': 0.5575, 'acc_stderr,none': 0.01110894141174761, 'alias': ' - paws_ja'}, 'paws_ko': {'acc,none': 0.552, 'acc_stderr,none': 0.011122493197456285, 'alias': ' - paws_ko'}, 'paws_zh': {'acc,none': 0.533, 'acc_stderr,none': 0.01115875256825067, 'alias': ' - paws_zh'}, 'lambada_multilingual': {'perplexity,none': 131.45396740665825, 'perplexity_stderr,none': 95.28024178884175, 'acc,none': 0.38490199883562976, 'acc_stderr,none': 0.07608898792977997, 'alias': 'lambada_multilingual'}, 'lambada_openai_mt_de': {'perplexity,none': 370.91952810475857, 'perplexity_stderr,none': 24.98299339282566, 'acc,none': 0.23015718998641568, 'acc_stderr,none': 0.0058644241714399855, 'alias': ' - lambada_openai_mt_de'}, 'lambada_openai_mt_en': {'perplexity,none': 6.583236525584539, 'perplexity_stderr,none': 0.17481189179976453, 'acc,none': 0.5717058024451775, 'acc_stderr,none': 0.0068939712541951454, 'alias': ' - lambada_openai_mt_en'}, 'lambada_openai_mt_es': {'perplexity,none': 51.02874715706533, 'perplexity_stderr,none': 2.6341920857292744, 'acc,none': 0.36638851154667185, 'acc_stderr,none': 0.0067126579546010565, 'alias': ' - lambada_openai_mt_es'}, 'lambada_openai_mt_fr': {'perplexity,none': 29.56217917543056, 'perplexity_stderr,none': 1.5411073949753211, 'acc,none': 0.4513875412381137, 'acc_stderr,none': 0.0069329758883686235, 'alias': ' - lambada_openai_mt_fr'}, 'lambada_openai_mt_it': {'perplexity,none': 199.1761460704524, 'perplexity_stderr,none': 13.648756866456297, 'acc,none': 0.30487094896176986, 'acc_stderr,none': 0.006413613926848421, 'alias': ' - lambada_openai_mt_it'}, 'xwinograd': {'acc,none': 0.7442121825129242, 'acc_stderr,none': 0.06414679137553342, 'alias': 'xwinograd'}, 'xwinograd_en': {'acc,none': 0.8219354838709677, 'acc_stderr,none': 0.007935777723887321, 'alias': ' - xwinograd_en'}, 'xwinograd_fr': {'acc,none': 0.6987951807228916, 'acc_stderr,none': 0.0506639425494172, 'alias': ' - xwinograd_fr'}, 'xwinograd_jp': {'acc,none': 0.6037539103232534, 'acc_stderr,none': 0.015802642616557255, 'alias': ' - xwinograd_jp'}, 'xwinograd_pt': {'acc,none': 0.7680608365019012, 'acc_stderr,none': 0.026075593860304693, 'alias': ' - xwinograd_pt'}, 'xwinograd_ru': {'acc,none': 0.5714285714285714, 'acc_stderr,none': 0.02792722339076032, 'alias': ' - xwinograd_ru'}, 'xwinograd_zh': {'acc,none': 0.7559523809523809, 'acc_stderr,none': 0.01915139944664688, 'alias': ' - xwinograd_zh'}, 'xstorycloze': {'acc,none': 0.5927441188857469, 'acc_stderr,none': 0.05262352730974911, 'alias': 'xstorycloze'}, 'xstorycloze_ar': {'acc,none': 0.5883520847121112, 'acc_stderr,none': 0.01266464832921408, 'alias': ' - xstorycloze_ar'}, 'xstorycloze_en': {'acc,none': 0.7081403044341495, 'acc_stderr,none': 0.01169925603764938, 'alias': ' - xstorycloze_en'}, 'xstorycloze_es': {'acc,none': 0.6598279285241562, 'acc_stderr,none': 0.012192034998028832, 'alias': ' - xstorycloze_es'}, 'xstorycloze_eu': {'acc,none': 0.57114493712773, 'acc_stderr,none': 0.012736202713147777, 'alias': ' - xstorycloze_eu'}, 'xstorycloze_hi': {'acc,none': 0.6048974189278623, 'acc_stderr,none': 0.012580772976133262, 'alias': ' - xstorycloze_hi'}, 'xstorycloze_id': {'acc,none': 0.6419589675711449, 'acc_stderr,none': 0.012337624883487575, 'alias': ' - xstorycloze_id'}, 'xstorycloze_my': {'acc,none': 0.48378557246856385, 'acc_stderr,none': 0.012860357805055867, 'alias': ' - xstorycloze_my'}, 'xstorycloze_ru': {'acc,none': 0.5268034414295168, 'acc_stderr,none': 0.012848623899505765, 'alias': ' - xstorycloze_ru'}, 'xstorycloze_sw': {'acc,none': 0.5413633355393779, 'acc_stderr,none': 0.012823020340169822, 'alias': ' - xstorycloze_sw'}, 'xstorycloze_te': {'acc,none': 0.5744540039708802, 'acc_stderr,none': 0.012723670419166326, 'alias': ' - xstorycloze_te'}, 'xstorycloze_zh': {'acc,none': 0.6194573130377233, 'acc_stderr,none': 0.012494500786685344, 'alias': ' - xstorycloze_zh'}}, 'groups': {'xcopa': {'acc,none': 0.5709090909090908, 'acc_stderr,none': 0.06135942275478038, 'alias': 'xcopa'}, 'xnli': {'acc,none': 0.41204819277108434, 'acc_stderr,none': 0.051535476594892576, 'alias': 'xnli'}, 'pawsx': {'acc,none': 0.5078571428571429, 'acc_stderr,none': 0.03988534011535243, 'alias': 'pawsx'}, 'lambada_multilingual': {'perplexity,none': 131.45396740665825, 'perplexity_stderr,none': 95.28024178884175, 'acc,none': 0.38490199883562976, 'acc_stderr,none': 0.07608898792977997, 'alias': 'lambada_multilingual'}, 'xwinograd': {'acc,none': 0.7442121825129242, 'acc_stderr,none': 0.06414679137553342, 'alias': 'xwinograd'}, 'xstorycloze': {'acc,none': 0.5927441188857469, 'acc_stderr,none': 0.05262352730974911, 'alias': 'xstorycloze'}}}}}\n"
+     ]
+    }
+   ],
+   "source": [
+    "import json\n",
+    "\n",
+    "# Global result map if it's not set\n",
+    "if 'global_result_map' not in globals():\n",
+    "    global_result_map = {}\n",
+    "\n",
+    "#\n",
+    "# Function to process the results.json file\n",
+    "#\n",
+    "def process_results_json(file_path):\n",
+    "    with open(file_path) as f:\n",
+    "        data = json.load(f)\n",
+    "\n",
+    "    # Model args, presplit by ','\n",
+    "    model_args = data['config']['model_args'].split(',')\n",
+    "\n",
+    "    # Extract the pretrained value from config.model_args\n",
+    "    modelname = model_args[0].split('=')[1]\n",
+    "\n",
+    "    # Opt array\n",
+    "    confArgsArr = model_args[1:]\n",
+    "\n",
+    "    # Sort the opt array\n",
+    "    confArgsArr.sort()\n",
+    "    # Convert it to a string\n",
+    "    confStr = ','.join(confArgsArr)\n",
+    "\n",
+    "    # Convert the option array of key=value strings to a dictionary\n",
+    "    confObj = { }\n",
+    "    for o in confArgsArr:\n",
+    "        k, v = o.split('=')\n",
+    "        confObj[k] = v\n",
+    "    \n",
+    "    # Create a dictionary to store the results, or use the existing one if it exists\n",
+    "    if modelname in global_result_map:\n",
+    "        modelObj = global_result_map[modelname]\n",
+    "    else:\n",
+    "        modelObj = {\n",
+    "            'name': modelname,\n",
+    "            'config': { }\n",
+    "        }\n",
+    "    \n",
+    "    # Get the opt object for the model\n",
+    "    if confStr in modelObj['config']:\n",
+    "        confSet = modelObj['config'][confStr]\n",
+    "    else:\n",
+    "        confSet = {\n",
+    "            'confStr': confStr,\n",
+    "            'confObj': confObj,\n",
+    "            'results': {},\n",
+    "            'groups': {}\n",
+    "        }\n",
+    "\n",
+    "    # Iterate over the results and extract the result object for each test/group\n",
+    "    if 'results' in data:\n",
+    "        for test, result in data['results'].items():\n",
+    "            confSet['results'][test] = result\n",
+    "    if 'groups' in data:\n",
+    "        for test, result in data['groups'].items():\n",
+    "            confSet['groups'][test] = result\n",
+    "    \n",
+    "    # Update the global result map object\n",
+    "    modelObj['config'][confStr] = confSet\n",
+    "    global_result_map[modelname] = modelObj\n",
+    "    return modelObj\n",
+    "\n",
+    "# Lets test the function with the first results.json file\n",
+    "first_result = process_results_json(results_json_files[0])\n",
+    "print(f\"Processed example: \", first_result)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Found 36 models\n",
+      "Models: \n",
+      "['bigscience/bloom-7b1', 'togethercomputer/RedPajama-INCITE-7B-Base', 'mistralai/Mistral-7B-v0.1', 'mosaicml/mpt-7b-instruct', 'mosaicml/mpt-7b', 'mosaicml/mpt-7b-chat', 'bigscience/bloomz-7b1-mt', 'bigscience/bloomz-7b1', 'EleutherAI/pythia-2.8b', 'EleutherAI/pythia-1.4b', 'EleutherAI/gpt-j-6b', 'EleutherAI/pythia-6.9b', 'microsoft/phi-1_5', 'microsoft/phi-2', 'microsoft/phi-1', 'allenai/OLMo-7B', 'TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T', 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', 'RWKV/rwkv-5-world-1b5', 'RWKV/rwkv-5-world-3b', 'RWKV/rwkv-4-world-3b', 'RWKV/rwkv-4-world-1b5', 'RWKV/rwkv-4-world-7b', 'RWKV/HF_v5-Eagle-7B', 'togethercomputer/RedPajama-INCITE-7B-Instruct', 'togethercomputer/RedPajama-INCITE-7B-Chat', 'facebook/opt-2.7b', 'facebook/opt-6.7b', 'facebook/opt-1.3b', 'tiiuae/falcon-7b-instruct', 'tiiuae/falcon-rw-1b', 'tiiuae/falcon-rw-7b', 'tiiuae/falcon-7b', 'huggyllama/llama-7b', 'meta-llama/Llama-2-7b-chat-hf', 'meta-llama/Llama-2-7b-hf']\n",
+      "Saved to compiled-lm-eval-results.json\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Lets reset and reprocess all the results.json files\n",
+    "global_result_map = {}\n",
+    "\n",
+    "# Process all the results.json files\n",
+    "for file in results_json_files:\n",
+    "    process_results_json(file)\n",
+    "\n",
+    "# Show high level list of models\n",
+    "print(f\"Found {len(global_result_map)} models\")\n",
+    "print(f\"Models: \\n{list(global_result_map.keys())}\")\n",
+    "\n",
+    "# Save the result map to a file\n",
+    "with open('summary/compiled-lm-eval-results.json', 'w') as f:\n",
+    "    json.dump(global_result_map, f, sort_keys=True, indent='\\t')\n",
+    "\n",
+    "# Echo that its been saved to json\n",
+    "print(f\"Saved to compiled-lm-eval-results.json\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Convert the results into CSV table formats"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "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>avg_acc</th>\n",
+       "      <th>avg_acc_stderr</th>\n",
+       "      <th>xcopa (acc)</th>\n",
+       "      <th>xcopa (acc_stderr)</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>bigscience/bloom-7b1</td>\n",
+       "      <td>0.570909</td>\n",
+       "      <td>0.061359</td>\n",
+       "      <td>0.570909</td>\n",
+       "      <td>0.061359</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>togethercomputer/RedPajama-INCITE-7B-Base</td>\n",
+       "      <td>0.525455</td>\n",
+       "      <td>0.036407</td>\n",
+       "      <td>0.525455</td>\n",
+       "      <td>0.036407</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>mistralai/Mistral-7B-v0.1</td>\n",
+       "      <td>0.558727</td>\n",
+       "      <td>0.055164</td>\n",
+       "      <td>0.558727</td>\n",
+       "      <td>0.055164</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>mosaicml/mpt-7b-instruct</td>\n",
+       "      <td>0.537091</td>\n",
+       "      <td>0.041919</td>\n",
+       "      <td>0.537091</td>\n",
+       "      <td>0.041919</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>mosaicml/mpt-7b</td>\n",
+       "      <td>0.536000</td>\n",
+       "      <td>0.042339</td>\n",
+       "      <td>0.536000</td>\n",
+       "      <td>0.042339</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>mosaicml/mpt-7b-chat</td>\n",
+       "      <td>0.538000</td>\n",
+       "      <td>0.047059</td>\n",
+       "      <td>0.538000</td>\n",
+       "      <td>0.047059</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>bigscience/bloomz-7b1-mt</td>\n",
+       "      <td>0.546000</td>\n",
+       "      <td>0.038321</td>\n",
+       "      <td>0.546000</td>\n",
+       "      <td>0.038321</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>bigscience/bloomz-7b1</td>\n",
+       "      <td>0.547818</td>\n",
+       "      <td>0.038920</td>\n",
+       "      <td>0.547818</td>\n",
+       "      <td>0.038920</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>EleutherAI/pythia-2.8b</td>\n",
+       "      <td>0.537455</td>\n",
+       "      <td>0.026941</td>\n",
+       "      <td>0.537455</td>\n",
+       "      <td>0.026941</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>EleutherAI/pythia-1.4b</td>\n",
+       "      <td>0.526545</td>\n",
+       "      <td>0.027441</td>\n",
+       "      <td>0.526545</td>\n",
+       "      <td>0.027441</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>EleutherAI/gpt-j-6b</td>\n",
+       "      <td>0.544182</td>\n",
+       "      <td>0.034404</td>\n",
+       "      <td>0.544182</td>\n",
+       "      <td>0.034404</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>EleutherAI/pythia-6.9b</td>\n",
+       "      <td>0.540545</td>\n",
+       "      <td>0.029689</td>\n",
+       "      <td>0.540545</td>\n",
+       "      <td>0.029689</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>microsoft/phi-1_5</td>\n",
+       "      <td>0.521636</td>\n",
+       "      <td>0.026198</td>\n",
+       "      <td>0.521636</td>\n",
+       "      <td>0.026198</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>microsoft/phi-2</td>\n",
+       "      <td>0.512182</td>\n",
+       "      <td>0.029742</td>\n",
+       "      <td>0.512182</td>\n",
+       "      <td>0.029742</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>microsoft/phi-1</td>\n",
+       "      <td>0.517636</td>\n",
+       "      <td>0.029612</td>\n",
+       "      <td>0.517636</td>\n",
+       "      <td>0.029612</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>allenai/OLMo-7B</td>\n",
+       "      <td>0.537818</td>\n",
+       "      <td>0.034147</td>\n",
+       "      <td>0.537818</td>\n",
+       "      <td>0.034147</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>TinyLlama/TinyLlama-1.1B-intermediate-step-143...</td>\n",
+       "      <td>0.529273</td>\n",
+       "      <td>0.029316</td>\n",
+       "      <td>0.529273</td>\n",
+       "      <td>0.029316</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>TinyLlama/TinyLlama-1.1B-Chat-v1.0</td>\n",
+       "      <td>0.528909</td>\n",
+       "      <td>0.031702</td>\n",
+       "      <td>0.528909</td>\n",
+       "      <td>0.031702</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>RWKV/rwkv-5-world-1b5</td>\n",
+       "      <td>0.578909</td>\n",
+       "      <td>0.045103</td>\n",
+       "      <td>0.578909</td>\n",
+       "      <td>0.045103</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>RWKV/rwkv-5-world-3b</td>\n",
+       "      <td>0.590182</td>\n",
+       "      <td>0.056241</td>\n",
+       "      <td>0.590182</td>\n",
+       "      <td>0.056241</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>RWKV/rwkv-4-world-3b</td>\n",
+       "      <td>0.575455</td>\n",
+       "      <td>0.040977</td>\n",
+       "      <td>0.575455</td>\n",
+       "      <td>0.040977</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>RWKV/rwkv-4-world-1b5</td>\n",
+       "      <td>0.554000</td>\n",
+       "      <td>0.039406</td>\n",
+       "      <td>0.554000</td>\n",
+       "      <td>0.039406</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>RWKV/rwkv-4-world-7b</td>\n",
+       "      <td>0.601455</td>\n",
+       "      <td>0.053116</td>\n",
+       "      <td>0.601455</td>\n",
+       "      <td>0.053116</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>RWKV/HF_v5-Eagle-7B</td>\n",
+       "      <td>0.621818</td>\n",
+       "      <td>0.068986</td>\n",
+       "      <td>0.621818</td>\n",
+       "      <td>0.068986</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>togethercomputer/RedPajama-INCITE-7B-Instruct</td>\n",
+       "      <td>0.528545</td>\n",
+       "      <td>0.036470</td>\n",
+       "      <td>0.528545</td>\n",
+       "      <td>0.036470</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>togethercomputer/RedPajama-INCITE-7B-Chat</td>\n",
+       "      <td>0.535455</td>\n",
+       "      <td>0.038723</td>\n",
+       "      <td>0.535455</td>\n",
+       "      <td>0.038723</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>facebook/opt-2.7b</td>\n",
+       "      <td>0.521818</td>\n",
+       "      <td>0.029821</td>\n",
+       "      <td>0.521818</td>\n",
+       "      <td>0.029821</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>facebook/opt-6.7b</td>\n",
+       "      <td>0.522909</td>\n",
+       "      <td>0.027216</td>\n",
+       "      <td>0.522909</td>\n",
+       "      <td>0.027216</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>facebook/opt-1.3b</td>\n",
+       "      <td>0.521818</td>\n",
+       "      <td>0.029112</td>\n",
+       "      <td>0.521818</td>\n",
+       "      <td>0.029112</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>tiiuae/falcon-7b-instruct</td>\n",
+       "      <td>0.536727</td>\n",
+       "      <td>0.053430</td>\n",
+       "      <td>0.536727</td>\n",
+       "      <td>0.053430</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>tiiuae/falcon-rw-1b</td>\n",
+       "      <td>0.522545</td>\n",
+       "      <td>0.029446</td>\n",
+       "      <td>0.522545</td>\n",
+       "      <td>0.029446</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>tiiuae/falcon-rw-7b</td>\n",
+       "      <td>0.535818</td>\n",
+       "      <td>0.033185</td>\n",
+       "      <td>0.535818</td>\n",
+       "      <td>0.033185</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>tiiuae/falcon-7b</td>\n",
+       "      <td>0.559636</td>\n",
+       "      <td>0.071650</td>\n",
+       "      <td>0.559636</td>\n",
+       "      <td>0.071650</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33</th>\n",
+       "      <td>huggyllama/llama-7b</td>\n",
+       "      <td>0.541818</td>\n",
+       "      <td>0.040718</td>\n",
+       "      <td>0.541818</td>\n",
+       "      <td>0.040718</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>34</th>\n",
+       "      <td>meta-llama/Llama-2-7b-chat-hf</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>35</th>\n",
+       "      <td>meta-llama/Llama-2-7b-hf</td>\n",
+       "      <td>0.566727</td>\n",
+       "      <td>0.052515</td>\n",
+       "      <td>0.566727</td>\n",
+       "      <td>0.052515</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                                model   avg_acc  \\\n",
+       "0                                bigscience/bloom-7b1  0.570909   \n",
+       "1           togethercomputer/RedPajama-INCITE-7B-Base  0.525455   \n",
+       "2                           mistralai/Mistral-7B-v0.1  0.558727   \n",
+       "3                            mosaicml/mpt-7b-instruct  0.537091   \n",
+       "4                                     mosaicml/mpt-7b  0.536000   \n",
+       "5                                mosaicml/mpt-7b-chat  0.538000   \n",
+       "6                            bigscience/bloomz-7b1-mt  0.546000   \n",
+       "7                               bigscience/bloomz-7b1  0.547818   \n",
+       "8                              EleutherAI/pythia-2.8b  0.537455   \n",
+       "9                              EleutherAI/pythia-1.4b  0.526545   \n",
+       "10                                EleutherAI/gpt-j-6b  0.544182   \n",
+       "11                             EleutherAI/pythia-6.9b  0.540545   \n",
+       "12                                  microsoft/phi-1_5  0.521636   \n",
+       "13                                    microsoft/phi-2  0.512182   \n",
+       "14                                    microsoft/phi-1  0.517636   \n",
+       "15                                    allenai/OLMo-7B  0.537818   \n",
+       "16  TinyLlama/TinyLlama-1.1B-intermediate-step-143...  0.529273   \n",
+       "17                 TinyLlama/TinyLlama-1.1B-Chat-v1.0  0.528909   \n",
+       "18                              RWKV/rwkv-5-world-1b5  0.578909   \n",
+       "19                               RWKV/rwkv-5-world-3b  0.590182   \n",
+       "20                               RWKV/rwkv-4-world-3b  0.575455   \n",
+       "21                              RWKV/rwkv-4-world-1b5  0.554000   \n",
+       "22                               RWKV/rwkv-4-world-7b  0.601455   \n",
+       "23                                RWKV/HF_v5-Eagle-7B  0.621818   \n",
+       "24      togethercomputer/RedPajama-INCITE-7B-Instruct  0.528545   \n",
+       "25          togethercomputer/RedPajama-INCITE-7B-Chat  0.535455   \n",
+       "26                                  facebook/opt-2.7b  0.521818   \n",
+       "27                                  facebook/opt-6.7b  0.522909   \n",
+       "28                                  facebook/opt-1.3b  0.521818   \n",
+       "29                          tiiuae/falcon-7b-instruct  0.536727   \n",
+       "30                                tiiuae/falcon-rw-1b  0.522545   \n",
+       "31                                tiiuae/falcon-rw-7b  0.535818   \n",
+       "32                                   tiiuae/falcon-7b  0.559636   \n",
+       "33                                huggyllama/llama-7b  0.541818   \n",
+       "34                      meta-llama/Llama-2-7b-chat-hf  0.000000   \n",
+       "35                           meta-llama/Llama-2-7b-hf  0.566727   \n",
+       "\n",
+       "    avg_acc_stderr  xcopa (acc)  xcopa (acc_stderr)  \n",
+       "0         0.061359     0.570909            0.061359  \n",
+       "1         0.036407     0.525455            0.036407  \n",
+       "2         0.055164     0.558727            0.055164  \n",
+       "3         0.041919     0.537091            0.041919  \n",
+       "4         0.042339     0.536000            0.042339  \n",
+       "5         0.047059     0.538000            0.047059  \n",
+       "6         0.038321     0.546000            0.038321  \n",
+       "7         0.038920     0.547818            0.038920  \n",
+       "8         0.026941     0.537455            0.026941  \n",
+       "9         0.027441     0.526545            0.027441  \n",
+       "10        0.034404     0.544182            0.034404  \n",
+       "11        0.029689     0.540545            0.029689  \n",
+       "12        0.026198     0.521636            0.026198  \n",
+       "13        0.029742     0.512182            0.029742  \n",
+       "14        0.029612     0.517636            0.029612  \n",
+       "15        0.034147     0.537818            0.034147  \n",
+       "16        0.029316     0.529273            0.029316  \n",
+       "17        0.031702     0.528909            0.031702  \n",
+       "18        0.045103     0.578909            0.045103  \n",
+       "19        0.056241     0.590182            0.056241  \n",
+       "20        0.040977     0.575455            0.040977  \n",
+       "21        0.039406     0.554000            0.039406  \n",
+       "22        0.053116     0.601455            0.053116  \n",
+       "23        0.068986     0.621818            0.068986  \n",
+       "24        0.036470     0.528545            0.036470  \n",
+       "25        0.038723     0.535455            0.038723  \n",
+       "26        0.029821     0.521818            0.029821  \n",
+       "27        0.027216     0.522909            0.027216  \n",
+       "28        0.029112     0.521818            0.029112  \n",
+       "29        0.053430     0.536727            0.053430  \n",
+       "30        0.029446     0.522545            0.029446  \n",
+       "31        0.033185     0.535818            0.033185  \n",
+       "32        0.071650     0.559636            0.071650  \n",
+       "33        0.040718     0.541818            0.040718  \n",
+       "34        0.000000          NaN                 NaN  \n",
+       "35        0.052515     0.566727            0.052515  "
+      ]
+     },
+     "execution_count": 56,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Lets convert this into a table, which we will display in this notebook, and save as a CSV\n",
+    "import pandas as pd\n",
+    "\n",
+    "##################################################\n",
+    "#\n",
+    "#  Utility functions\n",
+    "#\n",
+    "##################################################\n",
+    "\n",
+    "# Check if the given name string, is within the list, including \"*\" wildcard\n",
+    "def is_in_list(name, list):\n",
+    "    for n in list:\n",
+    "        if n[-1] == '*':\n",
+    "            if name.startswith(n[:-1]):\n",
+    "                return True\n",
+    "        elif n == name:\n",
+    "            return True\n",
+    "    return False\n",
+    "\n",
+    "# Is in inclusion exclusion list pair\n",
+    "def is_in_list_pair(name, inList, exList):\n",
+    "    if not is_in_list(name, inList):\n",
+    "        return False\n",
+    "    if is_in_list(name, exList):\n",
+    "        return False\n",
+    "    return True\n",
+    "\n",
+    "# Prepare a single test/group result object\n",
+    "# By applying common filtering and formatting changes\n",
+    "def prepare_test_result(result):\n",
+    "    # The reutrn object\n",
+    "    ret = {}\n",
+    "    # Iterate the result key/value\n",
+    "    for k, v in result.items():\n",
+    "        # Skip if its alias\n",
+    "        if k == 'alias':\n",
+    "            continue\n",
+    "\n",
+    "        # If the key ends with \",none\", drop the \",none\"\n",
+    "        if k.endswith(',none'):\n",
+    "            k = k[:-5]\n",
+    "        \n",
+    "        # Save the result\n",
+    "        ret[k] = v\n",
+    "    \n",
+    "    # Return the result\n",
+    "    return ret\n",
+    "\n",
+    "##################################################\n",
+    "#\n",
+    "#  Generate the result\n",
+    "#\n",
+    "##################################################\n",
+    "\n",
+    "# Create a list of rows for the table\n",
+    "def generate_result_table(\n",
+    "    inConfig = { \"dtype\": \"bfloat16\" },\n",
+    "\n",
+    "    # Results and groups to include\n",
+    "    inResults = [],\n",
+    "    inGroups = [\"*\"],\n",
+    "\n",
+    "    # Exclude results and groups, applied after inResults and inGroups\n",
+    "    exResults = [],\n",
+    "    exGroups = [],\n",
+    "\n",
+    "    # Sorted\n",
+    "    sort = False\n",
+    "):\n",
+    "    table_rows = []\n",
+    "\n",
+    "    # Iterate over the models\n",
+    "    for model, modelObj in global_result_map.items():\n",
+    "        # Iterate over the configurations\n",
+    "        for confStr, confSet in modelObj['config'].items():\n",
+    "            # Get the confObj\n",
+    "            confObj = confSet['confObj']\n",
+    "\n",
+    "            # Check if the inConfig, matches the confObj\n",
+    "            if inConfig:\n",
+    "                skip = False\n",
+    "                for k, v in inConfig.items():\n",
+    "                    if k not in confObj or confObj[k] != v:\n",
+    "                        skip = True\n",
+    "                        break\n",
+    "                if skip:\n",
+    "                    continue\n",
+    "\n",
+    "            # Create a row object\n",
+    "            row = {\n",
+    "                'model': model,\n",
+    "                # 'config': confStr\n",
+    "\n",
+    "                \"avg_acc\": 0.0,\n",
+    "                \"avg_acc_stderr\": 0.0,\n",
+    "            }\n",
+    "\n",
+    "            # Total acc / acc_stderr\n",
+    "            acc_total = 0.0\n",
+    "            acc_count = 0\n",
+    "            acc_stderr_total = 0.0\n",
+    "            acc_stderr_count = 0\n",
+    "\n",
+    "            # Add the groups\n",
+    "            for test, result in confSet['groups'].items():\n",
+    "\n",
+    "                # Skip if not in the inGroups or exGroups\n",
+    "                if not is_in_list_pair(test, inGroups, exGroups):\n",
+    "                    continue\n",
+    "\n",
+    "                # Filter the result obj\n",
+    "                cleanResult = prepare_test_result(result)\n",
+    "\n",
+    "                # Add the result to the row, as seperate columns for each key\n",
+    "                for k, v in cleanResult.items():\n",
+    "                    row[f\"{test} ({k})\"] = v\n",
+    "\n",
+    "                    if k == 'acc':\n",
+    "                        acc_total += v\n",
+    "                        acc_count += 1\n",
+    "                    elif k == 'acc_stderr':\n",
+    "                        acc_stderr_total += v\n",
+    "                        acc_stderr_count += 1\n",
+    "\n",
+    "            # Add the results\n",
+    "            for test, result in confSet['results'].items():\n",
+    "\n",
+    "                # Skip if not in the inResults or exResults\n",
+    "                if not is_in_list_pair(test, inResults, exResults):\n",
+    "                    continue\n",
+    "\n",
+    "                # Filter the result obj\n",
+    "                cleanResult = prepare_test_result(result)\n",
+    "\n",
+    "                # Add the result to the row, as seperate columns for each key\n",
+    "                for k, v in cleanResult.items():\n",
+    "                    row[f\"{test} ({k})\"] = v\n",
+    "\n",
+    "                    if k == 'acc':\n",
+    "                        acc_total += v\n",
+    "                        acc_count += 1\n",
+    "                    elif k == 'acc_stderr':\n",
+    "                        acc_stderr_total += v\n",
+    "                        acc_stderr_count += 1\n",
+    "                \n",
+    "            # Add the avg acc and acc_stderr\n",
+    "            if acc_count > 0:\n",
+    "               row[\"avg_acc\"] = acc_total / acc_count\n",
+    "            if acc_stderr_count > 0:\n",
+    "                row[\"avg_acc_stderr\"] = acc_stderr_total / acc_stderr_count\n",
+    "\n",
+    "            # Append the row to the table\n",
+    "            table_rows.append(row)\n",
+    "\n",
+    "    # Create a dataframe from the table rows\n",
+    "    df = pd.DataFrame(table_rows)\n",
+    "\n",
+    "    # Sort by avg_acc\n",
+    "    if sort:\n",
+    "        df = df.sort_values(by='avg_acc', ascending=False)\n",
+    "\n",
+    "    # Show the dataframe\n",
+    "    return df\n",
+    "\n",
+    "# Generate the dataframe\n",
+    "df = generate_result_table( inConfig = { \"dtype\": \"bfloat16\" }, inGroups=[\"xcopa\"], inResults=[] )\n",
+    "\n",
+    "# # Save the dataframe to a CSV file\n",
+    "# df.to_csv('summary/compiled-lm-eval-results.csv', index=False)\n",
+    "\n",
+    "# Show results\n",
+    "df\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "total 13472\n",
+      "-rw-r--r--@ 1 picocreator  staff   841504 Feb 22 13:33 bf16-all-results-and-groups.csv\n",
+      "-rw-r--r--  1 picocreator  staff   768190 Feb 22 13:33 bf16-eng-results.csv\n",
+      "-rw-r--r--@ 1 picocreator  staff    64695 Feb 22 13:33 bf16-eng-summary.csv\n",
+      "-rw-r--r--@ 1 picocreator  staff    85450 Feb 22 13:33 bf16-multilang-results.csv\n",
+      "-rw-r--r--@ 1 picocreator  staff    12083 Feb 22 13:33 bf16-multilang-summary.csv\n",
+      "-rw-r--r--  1 picocreator  staff   768190 Feb 22 13:33 bf16-sorted-eng-results.csv\n",
+      "-rw-r--r--  1 picocreator  staff    12083 Feb 22 13:33 bf16-sorted-multilang-summary.csv\n",
+      "-rw-r--r--  1 picocreator  staff  3296588 Feb 22 13:29 compiled-lm-eval-results.json\n"
+     ]
+    }
+   ],
+   "source": [
+    "##################################################\n",
+    "#\n",
+    "#  Build the various subsets\n",
+    "#\n",
+    "##################################################\n",
+    "\n",
+    "# Overall results\n",
+    "all_results = generate_result_table( inConfig = { \"dtype\": \"bfloat16\" }, inGroups=[\"*\"], inResults=[\"*\"] )\n",
+    "all_results.to_csv('summary/bf16-all-results-and-groups.csv', index=False)\n",
+    "\n",
+    "# Multilang results\n",
+    "multiLang_tTest = [\"xcopa_*\", \"xnli_*\", \"xstorycloze_*\", \"xwinograd_*\", \"lambada_openai_*\",     \"pawsx_*\"]\n",
+    "multiLang_tGrps = [\"xcopa\",   \"xnli\",   \"xstorycloze\",   \"xwinograd\",   \"lambada_multilingual\", \"pawsx\"]\n",
+    "\n",
+    "multilang_grp = generate_result_table( inConfig = { \"dtype\": \"bfloat16\" }, inGroups=multiLang_tGrps, inResults=[] )\n",
+    "multilang_test = generate_result_table( inConfig = { \"dtype\": \"bfloat16\" }, inGroups=multiLang_tGrps, inResults=multiLang_tTest )\n",
+    "multilang_grp.to_csv('summary/bf16-multilang-summary.csv', index=False)\n",
+    "multilang_test.to_csv('summary/bf16-multilang-results.csv', index=False)\n",
+    "\n",
+    "multilang_grp_sorted = generate_result_table( inConfig = { \"dtype\": \"bfloat16\" }, inGroups=multiLang_tGrps, inResults=[], sort=True )\n",
+    "multilang_grp_sorted.to_csv('summary/bf16-sorted-multilang-summary.csv', index=False)\n",
+    "\n",
+    "# All other results\n",
+    "eng_grp = generate_result_table( inConfig = { \"dtype\": \"bfloat16\" }, inGroups=[\"*\"], inResults=[], exGroups=multiLang_tGrps )\n",
+    "eng_test = generate_result_table( inConfig = { \"dtype\": \"bfloat16\" }, inGroups=[\"*\"], inResults=[\"*\"], exGroups=multiLang_tGrps, exResults=multiLang_tTest )\n",
+    "eng_test_sorted = generate_result_table( inConfig = { \"dtype\": \"bfloat16\" }, inGroups=[\"*\"], inResults=[\"*\"], exGroups=multiLang_tGrps, exResults=multiLang_tTest, sort=True )\n",
+    "\n",
+    "eng_grp.to_csv('summary/bf16-eng-summary.csv', index=False)\n",
+    "eng_test.to_csv('summary/bf16-eng-results.csv', index=False)\n",
+    "eng_test_sorted.to_csv('summary/bf16-sorted-eng-results.csv', index=False)\n",
+    "\n",
+    "# List the files\n",
+    "!ls -lh summary"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "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": "3.9.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

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