demo/summarize_by_passk.ipynb

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  {
   "cell_type": "markdown",
   "id": "c217f162-d86d-489f-b6a8-6bd82a98181a",
   "metadata": {},
   "source": [
    "# pass@k analysis\n",
    "This notebook demonstrates how to visualize which model managed to achieve which pass@k value."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d7c80449-8b7b-41a7-a92c-f7edfd443e46",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c7abf5c6-62ac-4597-8aec-b5b9ab9503b3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "samples_claude-3-5-sonnet-20240620_passk_results.csv\n",
      "samples_claude-3-opus-20240229_passk_results.csv\n",
      "samples_codegemma-7b-instruct-fp16_passk_results.csv\n",
      "samples_codellama-70b-instruct-q4_0_passk_results.csv\n",
      "samples_codellama_passk_results.csv\n",
      "samples_command-r-plus-104b-q4_0_passk_results.csv\n",
      "samples_deepseek-coder-v2_passk_results.csv\n",
      "samples_gemini-1.5-flash-001_passk_results.csv\n",
      "samples_gemini-1.5-pro-001_passk_results.csv\n",
      "samples_gemini-pro_passk_results.csv\n",
      "samples_gpt-3.5-turbo-1106_passk_results.csv\n",
      "samples_gpt-4-1106-preview_passk_results.csv\n",
      "samples_gpt-4-turbo-2024-04-09_passk_results.csv\n",
      "samples_gpt-4o-2024-05-13_passk_results.csv\n",
      "samples_gpt-4o-mini-2024-07-18_passk_results.csv\n",
      "samples_llama3-70b-instruct-q4_0_passk_results.csv\n",
      "samples_llama3-70b-instruct-q8_0_passk_results.csv\n",
      "samples_llama3-8b-instruct-fp16_passk_results.csv\n",
      "samples_mistral-nemo_passk_results.csv\n",
      "samples_mixtral-8x22b-instruct-v0.1-q4_0_passk_results.csv\n",
      "samples_mixtral-8x7b-instruct-v0.1-q5_0_passk_results.csv\n",
      "samples_phi3-3.8b-mini-instruct-4k-fp16_passk_results.csv\n",
      "samples_reference_passk_results.csv\n"
     ]
    }
   ],
   "source": [
    "directory = \"../data/\"\n",
    "\n",
    "collection = []\n",
    "for filename in os.listdir(directory):\n",
    "    if filename.endswith(\".csv\"):\n",
    "        print(filename)\n",
    "        df = pd.read_csv(directory + filename)\n",
    "        df['model'] = filename.replace(\"_passk_results.csv\", \"\").replace(\"samples_\", \"\")\n",
    "        collection.append(df)\n",
    "\n",
    "df = pd.concat(collection)"
   ]
  },
  {
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   "execution_count": 3,
   "id": "a2cceb48-c75c-4b76-a984-322f3a055062",
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       "   Unnamed: 0    pass@1    pass@5   pass@10                             model\n",
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       "0           0  0.087719  0.300543  0.456140                         codellama\n",
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       "0           0  0.143860  0.341618  0.403509           llama3-8b-instruct-fp16\n",
       "0           0  0.152632  0.359649  0.508772                      mistral-nemo\n",
       "0           0  0.243860  0.514690  0.666667  mixtral-8x22b-instruct-v0.1-q4_0\n",
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       "0           0  0.180702  0.421540  0.508772   phi3-3.8b-mini-instruct-4k-fp16\n",
       "0           0  1.000000  1.000000  1.000000                         reference"
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     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
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   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e5544292-bf62-495d-8be7-4ab493c71aed",
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       "      <td>0.143860</td>\n",
       "      <td>0.341618</td>\n",
       "      <td>0.403509</td>\n",
       "      <td>llama3-8b-instruct-fp16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.122807</td>\n",
       "      <td>0.384781</td>\n",
       "      <td>0.526316</td>\n",
       "      <td>command-r-plus-104b-q4_0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.087719</td>\n",
       "      <td>0.300543</td>\n",
       "      <td>0.456140</td>\n",
       "      <td>codellama</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     pass@1    pass@5   pass@10                             model\n",
       "0  1.000000  1.000000  1.000000                         reference\n",
       "0  0.580702  0.747911  0.789474        claude-3-5-sonnet-20240620\n",
       "0  0.508772  0.694932  0.754386                 gpt-4o-2024-05-13\n",
       "0  0.473684  0.686090  0.736842            gpt-4-turbo-2024-04-09\n",
       "0  0.470175  0.654135  0.684211            claude-3-opus-20240229\n",
       "0  0.464912  0.678850  0.719298                gpt-4-1106-preview\n",
       "0  0.459649  0.603801  0.649123                gemini-1.5-pro-001\n",
       "0  0.428070  0.631649  0.684211            gpt-4o-mini-2024-07-18\n",
       "0  0.368421  0.642161  0.719298                 deepseek-coder-v2\n",
       "0  0.364912  0.615497  0.719298          llama3-70b-instruct-q8_0\n",
       "0  0.354386  0.624687  0.736842          llama3-70b-instruct-q4_0\n",
       "0  0.333333  0.553676  0.701754                gpt-3.5-turbo-1106\n",
       "0  0.294737  0.448761  0.543860              gemini-1.5-flash-001\n",
       "0  0.249123  0.494291  0.578947        codegemma-7b-instruct-fp16\n",
       "0  0.243860  0.514690  0.666667  mixtral-8x22b-instruct-v0.1-q4_0\n",
       "0  0.207018  0.485171  0.578947   mixtral-8x7b-instruct-v0.1-q5_0\n",
       "0  0.180702  0.421540  0.508772   phi3-3.8b-mini-instruct-4k-fp16\n",
       "0  0.177193  0.497633  0.631579       codellama-70b-instruct-q4_0\n",
       "0  0.173684  0.353523  0.438596                        gemini-pro\n",
       "0  0.152632  0.359649  0.508772                      mistral-nemo\n",
       "0  0.143860  0.341618  0.403509           llama3-8b-instruct-fp16\n",
       "0  0.122807  0.384781  0.526316          command-r-plus-104b-q4_0\n",
       "0  0.087719  0.300543  0.456140                         codellama"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Drop the \"Unnamed: 0\" column from the dataframe\n",
    "df = df.drop(\"Unnamed: 0\", axis=1)\n",
    "df = df.sort_values(\"pass@1\", ascending=False)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e09d98ea-7fc8-4004-9382-f9a02765b052",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\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>model</th>\n",
       "      <th>reference</th>\n",
       "      <th>claude-3-5-sonnet-20240620</th>\n",
       "      <th>gpt-4o-2024-05-13</th>\n",
       "      <th>gpt-4-turbo-2024-04-09</th>\n",
       "      <th>claude-3-opus-20240229</th>\n",
       "      <th>gpt-4-1106-preview</th>\n",
       "      <th>gemini-1.5-pro-001</th>\n",
       "      <th>gpt-4o-mini-2024-07-18</th>\n",
       "      <th>deepseek-coder-v2</th>\n",
       "      <th>llama3-70b-instruct-q8_0</th>\n",
       "      <th>...</th>\n",
       "      <th>mixtral-8x22b-instruct-v0.1-q4_0</th>\n",
       "      <th>mixtral-8x7b-instruct-v0.1-q5_0</th>\n",
       "      <th>phi3-3.8b-mini-instruct-4k-fp16</th>\n",
       "      <th>codellama-70b-instruct-q4_0</th>\n",
       "      <th>gemini-pro</th>\n",
       "      <th>mistral-nemo</th>\n",
       "      <th>llama3-8b-instruct-fp16</th>\n",
       "      <th>command-r-plus-104b-q4_0</th>\n",
       "      <th>codellama</th>\n",
       "      <th>k</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>pass@1</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.580702</td>\n",
       "      <td>0.508772</td>\n",
       "      <td>0.473684</td>\n",
       "      <td>0.470175</td>\n",
       "      <td>0.464912</td>\n",
       "      <td>0.459649</td>\n",
       "      <td>0.428070</td>\n",
       "      <td>0.368421</td>\n",
       "      <td>0.364912</td>\n",
       "      <td>...</td>\n",
       "      <td>0.243860</td>\n",
       "      <td>0.207018</td>\n",
       "      <td>0.180702</td>\n",
       "      <td>0.177193</td>\n",
       "      <td>0.173684</td>\n",
       "      <td>0.152632</td>\n",
       "      <td>0.143860</td>\n",
       "      <td>0.122807</td>\n",
       "      <td>0.087719</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pass@5</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.747911</td>\n",
       "      <td>0.694932</td>\n",
       "      <td>0.686090</td>\n",
       "      <td>0.654135</td>\n",
       "      <td>0.678850</td>\n",
       "      <td>0.603801</td>\n",
       "      <td>0.631649</td>\n",
       "      <td>0.642161</td>\n",
       "      <td>0.615497</td>\n",
       "      <td>...</td>\n",
       "      <td>0.514690</td>\n",
       "      <td>0.485171</td>\n",
       "      <td>0.421540</td>\n",
       "      <td>0.497633</td>\n",
       "      <td>0.353523</td>\n",
       "      <td>0.359649</td>\n",
       "      <td>0.341618</td>\n",
       "      <td>0.384781</td>\n",
       "      <td>0.300543</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pass@10</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.789474</td>\n",
       "      <td>0.754386</td>\n",
       "      <td>0.736842</td>\n",
       "      <td>0.684211</td>\n",
       "      <td>0.719298</td>\n",
       "      <td>0.649123</td>\n",
       "      <td>0.684211</td>\n",
       "      <td>0.719298</td>\n",
       "      <td>0.719298</td>\n",
       "      <td>...</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>0.578947</td>\n",
       "      <td>0.508772</td>\n",
       "      <td>0.631579</td>\n",
       "      <td>0.438596</td>\n",
       "      <td>0.508772</td>\n",
       "      <td>0.403509</td>\n",
       "      <td>0.526316</td>\n",
       "      <td>0.456140</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "model    reference  claude-3-5-sonnet-20240620  gpt-4o-2024-05-13  \\\n",
       "pass@1         1.0                    0.580702           0.508772   \n",
       "pass@5         1.0                    0.747911           0.694932   \n",
       "pass@10        1.0                    0.789474           0.754386   \n",
       "\n",
       "model    gpt-4-turbo-2024-04-09  claude-3-opus-20240229  gpt-4-1106-preview  \\\n",
       "pass@1                 0.473684                0.470175            0.464912   \n",
       "pass@5                 0.686090                0.654135            0.678850   \n",
       "pass@10                0.736842                0.684211            0.719298   \n",
       "\n",
       "model    gemini-1.5-pro-001  gpt-4o-mini-2024-07-18  deepseek-coder-v2  \\\n",
       "pass@1             0.459649                0.428070           0.368421   \n",
       "pass@5             0.603801                0.631649           0.642161   \n",
       "pass@10            0.649123                0.684211           0.719298   \n",
       "\n",
       "model    llama3-70b-instruct-q8_0  ...  mixtral-8x22b-instruct-v0.1-q4_0  \\\n",
       "pass@1                   0.364912  ...                          0.243860   \n",
       "pass@5                   0.615497  ...                          0.514690   \n",
       "pass@10                  0.719298  ...                          0.666667   \n",
       "\n",
       "model    mixtral-8x7b-instruct-v0.1-q5_0  phi3-3.8b-mini-instruct-4k-fp16  \\\n",
       "pass@1                          0.207018                         0.180702   \n",
       "pass@5                          0.485171                         0.421540   \n",
       "pass@10                         0.578947                         0.508772   \n",
       "\n",
       "model    codellama-70b-instruct-q4_0  gemini-pro  mistral-nemo  \\\n",
       "pass@1                      0.177193    0.173684      0.152632   \n",
       "pass@5                      0.497633    0.353523      0.359649   \n",
       "pass@10                     0.631579    0.438596      0.508772   \n",
       "\n",
       "model    llama3-8b-instruct-fp16  command-r-plus-104b-q4_0  codellama   k  \n",
       "pass@1                  0.143860                  0.122807   0.087719   1  \n",
       "pass@5                  0.341618                  0.384781   0.300543   5  \n",
       "pass@10                 0.403509                  0.526316   0.456140  10  \n",
       "\n",
       "[3 rows x 24 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Set the \"model\" column as the index and then transpose\n",
    "df_transposed = df.set_index('model').transpose()\n",
    "df_transposed['k'] = [1,5,10]\n",
    "df_transposed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "14bc43f6",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "aae3266d-e23f-4231-ab82-866dc60d3249",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "     pass@1    pass@5   pass@10                             model\n",
      "0  1.000000  1.000000  1.000000                         reference\n",
      "0  0.580702  0.747911  0.789474        claude-3-5-sonnet-20240620\n",
      "0  0.508772  0.694932  0.754386                 gpt-4o-2024-05-13\n",
      "0  0.473684  0.686090  0.736842            gpt-4-turbo-2024-04-09\n",
      "0  0.470175  0.654135  0.684211            claude-3-opus-20240229\n",
      "0  0.464912  0.678850  0.719298                gpt-4-1106-preview\n",
      "0  0.459649  0.603801  0.649123                gemini-1.5-pro-001\n",
      "0  0.428070  0.631649  0.684211            gpt-4o-mini-2024-07-18\n",
      "0  0.368421  0.642161  0.719298                 deepseek-coder-v2\n",
      "0  0.364912  0.615497  0.719298          llama3-70b-instruct-q8_0\n",
      "0  0.354386  0.624687  0.736842          llama3-70b-instruct-q4_0\n",
      "0  0.333333  0.553676  0.701754                gpt-3.5-turbo-1106\n",
      "0  0.294737  0.448761  0.543860              gemini-1.5-flash-001\n",
      "0  0.249123  0.494291  0.578947        codegemma-7b-instruct-fp16\n",
      "0  0.243860  0.514690  0.666667  mixtral-8x22b-instruct-v0.1-q4_0\n",
      "0  0.207018  0.485171  0.578947   mixtral-8x7b-instruct-v0.1-q5_0\n",
      "0  0.180702  0.421540  0.508772   phi3-3.8b-mini-instruct-4k-fp16\n",
      "0  0.177193  0.497633  0.631579       codellama-70b-instruct-q4_0\n",
      "0  0.173684  0.353523  0.438596                        gemini-pro\n",
      "0  0.152632  0.359649  0.508772                      mistral-nemo\n",
      "0  0.143860  0.341618  0.403509           llama3-8b-instruct-fp16\n",
      "0  0.122807  0.384781  0.526316          command-r-plus-104b-q4_0\n",
      "0  0.087719  0.300543  0.456140                         codellama\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "sns.set_style(\"white\")\n",
    "\n",
    "\n",
    "# Assuming 'k' is an index after transposition, let's reset the index first if not already done\n",
    "if 'k' not in df_transposed.columns:\n",
    "    df_transposed.reset_index(inplace=True)\n",
    "print(df)\n",
    "# Separate 'k' column for x-axis\n",
    "x = df_transposed['k']\n",
    "vals = df_transposed.drop('k', axis=1)\n",
    "fig = plt.figure(figsize=(6,6))\n",
    "g = sns.lineplot(vals, palette=\"Set3\", dashes=False, linewidth=2)\n",
    "sns.despine(offset=10, trim=True);\n",
    "g.set_xticklabels(x)\n",
    "\n",
    "# Adding plot decorations\n",
    "plt.xlabel('k')\n",
    "plt.ylabel('Pass rate')\n",
    "plt.title('Pass rates depending on k')\n",
    "plt.legend(title='LLMs', bbox_to_anchor=(1.05, 1), loc='upper left')\n",
    "plt.tight_layout()\n",
    "\n",
    "plt.savefig(\"../docs/paper/pass_k_llms_plot.png\", dpi=300, bbox_inches='tight')\n",
    "plt.show()"
   ]
  },
  {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>model</th>\n",
       "      <th>reference</th>\n",
       "      <th>claude-3-5-sonnet-20240620</th>\n",
       "      <th>gpt-4o-2024-05-13</th>\n",
       "      <th>gpt-4-turbo-2024-04-09</th>\n",
       "      <th>claude-3-opus-20240229</th>\n",
       "      <th>gpt-4-1106-preview</th>\n",
       "      <th>gemini-1.5-pro-001</th>\n",
       "      <th>gpt-4o-mini-2024-07-18</th>\n",
       "      <th>deepseek-coder-v2</th>\n",
       "      <th>llama3-70b-instruct-q8_0</th>\n",
       "      <th>...</th>\n",
       "      <th>codegemma-7b-instruct-fp16</th>\n",
       "      <th>mixtral-8x22b-instruct-v0.1-q4_0</th>\n",
       "      <th>mixtral-8x7b-instruct-v0.1-q5_0</th>\n",
       "      <th>phi3-3.8b-mini-instruct-4k-fp16</th>\n",
       "      <th>codellama-70b-instruct-q4_0</th>\n",
       "      <th>gemini-pro</th>\n",
       "      <th>mistral-nemo</th>\n",
       "      <th>llama3-8b-instruct-fp16</th>\n",
       "      <th>command-r-plus-104b-q4_0</th>\n",
       "      <th>codellama</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>pass@1</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.580702</td>\n",
       "      <td>0.508772</td>\n",
       "      <td>0.473684</td>\n",
       "      <td>0.470175</td>\n",
       "      <td>0.464912</td>\n",
       "      <td>0.459649</td>\n",
       "      <td>0.428070</td>\n",
       "      <td>0.368421</td>\n",
       "      <td>0.364912</td>\n",
       "      <td>...</td>\n",
       "      <td>0.249123</td>\n",
       "      <td>0.243860</td>\n",
       "      <td>0.207018</td>\n",
       "      <td>0.180702</td>\n",
       "      <td>0.177193</td>\n",
       "      <td>0.173684</td>\n",
       "      <td>0.152632</td>\n",
       "      <td>0.143860</td>\n",
       "      <td>0.122807</td>\n",
       "      <td>0.087719</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pass@5</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.747911</td>\n",
       "      <td>0.694932</td>\n",
       "      <td>0.686090</td>\n",
       "      <td>0.654135</td>\n",
       "      <td>0.678850</td>\n",
       "      <td>0.603801</td>\n",
       "      <td>0.631649</td>\n",
       "      <td>0.642161</td>\n",
       "      <td>0.615497</td>\n",
       "      <td>...</td>\n",
       "      <td>0.494291</td>\n",
       "      <td>0.514690</td>\n",
       "      <td>0.485171</td>\n",
       "      <td>0.421540</td>\n",
       "      <td>0.497633</td>\n",
       "      <td>0.353523</td>\n",
       "      <td>0.359649</td>\n",
       "      <td>0.341618</td>\n",
       "      <td>0.384781</td>\n",
       "      <td>0.300543</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pass@10</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.789474</td>\n",
       "      <td>0.754386</td>\n",
       "      <td>0.736842</td>\n",
       "      <td>0.684211</td>\n",
       "      <td>0.719298</td>\n",
       "      <td>0.649123</td>\n",
       "      <td>0.684211</td>\n",
       "      <td>0.719298</td>\n",
       "      <td>0.719298</td>\n",
       "      <td>...</td>\n",
       "      <td>0.578947</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>0.578947</td>\n",
       "      <td>0.508772</td>\n",
       "      <td>0.631579</td>\n",
       "      <td>0.438596</td>\n",
       "      <td>0.508772</td>\n",
       "      <td>0.403509</td>\n",
       "      <td>0.526316</td>\n",
       "      <td>0.456140</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "model    reference  claude-3-5-sonnet-20240620  gpt-4o-2024-05-13  \\\n",
       "pass@1         1.0                    0.580702           0.508772   \n",
       "pass@5         1.0                    0.747911           0.694932   \n",
       "pass@10        1.0                    0.789474           0.754386   \n",
       "\n",
       "model    gpt-4-turbo-2024-04-09  claude-3-opus-20240229  gpt-4-1106-preview  \\\n",
       "pass@1                 0.473684                0.470175            0.464912   \n",
       "pass@5                 0.686090                0.654135            0.678850   \n",
       "pass@10                0.736842                0.684211            0.719298   \n",
       "\n",
       "model    gemini-1.5-pro-001  gpt-4o-mini-2024-07-18  deepseek-coder-v2  \\\n",
       "pass@1             0.459649                0.428070           0.368421   \n",
       "pass@5             0.603801                0.631649           0.642161   \n",
       "pass@10            0.649123                0.684211           0.719298   \n",
       "\n",
       "model    llama3-70b-instruct-q8_0  ...  codegemma-7b-instruct-fp16  \\\n",
       "pass@1                   0.364912  ...                    0.249123   \n",
       "pass@5                   0.615497  ...                    0.494291   \n",
       "pass@10                  0.719298  ...                    0.578947   \n",
       "\n",
       "model    mixtral-8x22b-instruct-v0.1-q4_0  mixtral-8x7b-instruct-v0.1-q5_0  \\\n",
       "pass@1                           0.243860                         0.207018   \n",
       "pass@5                           0.514690                         0.485171   \n",
       "pass@10                          0.666667                         0.578947   \n",
       "\n",
       "model    phi3-3.8b-mini-instruct-4k-fp16  codellama-70b-instruct-q4_0  \\\n",
       "pass@1                          0.180702                     0.177193   \n",
       "pass@5                          0.421540                     0.497633   \n",
       "pass@10                         0.508772                     0.631579   \n",
       "\n",
       "model    gemini-pro  mistral-nemo  llama3-8b-instruct-fp16  \\\n",
       "pass@1     0.173684      0.152632                 0.143860   \n",
       "pass@5     0.353523      0.359649                 0.341618   \n",
       "pass@10    0.438596      0.508772                 0.403509   \n",
       "\n",
       "model    command-r-plus-104b-q4_0  codellama  \n",
       "pass@1                   0.122807   0.087719  \n",
       "pass@5                   0.384781   0.300543  \n",
       "pass@10                  0.526316   0.456140  \n",
       "\n",
       "[3 rows x 23 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_transposed.drop('k', axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3f3592f5",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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