diff --git "a/zephyr-7b-beta-inc/inference_innocean_demo_240221(TG).ipynb" "b/zephyr-7b-beta-inc/inference_innocean_demo_240221(TG).ipynb"
new file mode 100644--- /dev/null
+++ "b/zephyr-7b-beta-inc/inference_innocean_demo_240221(TG).ipynb"
@@ -0,0 +1,10266 @@
+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "ldo7vN9_yfm2"
+      },
+      "source": [
+        "환경설정(Colab 내 한글 오류 제거)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 1,
+      "metadata": {
+        "id": "scNoqBhEyhfV"
+      },
+      "outputs": [],
+      "source": [
+        "import locale\n",
+        "def getpreferredencoding(do_setlocale = True):\n",
+        "    return \"UTF-8\"\n",
+        "locale.getpreferredencoding = getpreferredencoding"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "muzP7Pygx-sa"
+      },
+      "source": [
+        "baseline model(HuggingFaceH4/zephyr-7b-alpha) & framework 다운로드"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 2,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "JKyH9LK_w6R3",
+        "outputId": "95aac920-3208-42cc-9643-e81dca6a470d"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Requirement already satisfied: transformers in /usr/local/lib/python3.10/dist-packages (4.37.2)\n",
+            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from transformers) (3.13.1)\n",
+            "Requirement already satisfied: huggingface-hub<1.0,>=0.19.3 in /usr/local/lib/python3.10/dist-packages (from transformers) (0.20.3)\n",
+            "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from transformers) (1.25.2)\n",
+            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from transformers) (23.2)\n",
+            "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from transformers) (6.0.1)\n",
+            "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.10/dist-packages (from transformers) (2023.12.25)\n",
+            "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from transformers) (2.31.0)\n",
+            "Requirement already satisfied: tokenizers<0.19,>=0.14 in /usr/local/lib/python3.10/dist-packages (from transformers) (0.15.2)\n",
+            "Requirement already satisfied: safetensors>=0.4.1 in /usr/local/lib/python3.10/dist-packages (from transformers) (0.4.2)\n",
+            "Requirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.10/dist-packages (from transformers) (4.66.2)\n",
+            "Requirement already satisfied: fsspec>=2023.5.0 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.19.3->transformers) (2023.6.0)\n",
+            "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.19.3->transformers) (4.9.0)\n",
+            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (3.3.2)\n",
+            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (3.6)\n",
+            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (2.0.7)\n",
+            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (2024.2.2)\n"
+          ]
+        }
+      ],
+      "source": [
+        "!pip install transformers"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 3,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "NqFqCDwoxSFx",
+        "outputId": "71310549-36d2-4c34-9a93-6d4f2ffa1ca9"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Collecting accelerate\n",
+            "  Downloading accelerate-0.27.2-py3-none-any.whl (279 kB)\n",
+            "\u001b[?25l     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/280.0 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K     \u001b[91m━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[90m╺\u001b[0m\u001b[90m━━━━━━━━━━━━━\u001b[0m \u001b[32m184.3/280.0 kB\u001b[0m \u001b[31m5.4 MB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0m\r\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m280.0/280.0 kB\u001b[0m \u001b[31m6.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hRequirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from accelerate) (1.25.2)\n",
+            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from accelerate) (23.2)\n",
+            "Requirement already satisfied: psutil in /usr/local/lib/python3.10/dist-packages (from accelerate) (5.9.5)\n",
+            "Requirement already satisfied: pyyaml in /usr/local/lib/python3.10/dist-packages (from accelerate) (6.0.1)\n",
+            "Requirement already satisfied: torch>=1.10.0 in /usr/local/lib/python3.10/dist-packages (from accelerate) (2.1.0+cu121)\n",
+            "Requirement already satisfied: huggingface-hub in /usr/local/lib/python3.10/dist-packages (from accelerate) (0.20.3)\n",
+            "Requirement already satisfied: safetensors>=0.3.1 in /usr/local/lib/python3.10/dist-packages (from accelerate) (0.4.2)\n",
+            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (3.13.1)\n",
+            "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (4.9.0)\n",
+            "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (1.12)\n",
+            "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (3.2.1)\n",
+            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (3.1.3)\n",
+            "Requirement already satisfied: fsspec in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (2023.6.0)\n",
+            "Requirement already satisfied: triton==2.1.0 in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (2.1.0)\n",
+            "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from huggingface-hub->accelerate) (2.31.0)\n",
+            "Requirement already satisfied: tqdm>=4.42.1 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub->accelerate) (4.66.2)\n",
+            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch>=1.10.0->accelerate) (2.1.5)\n",
+            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub->accelerate) (3.3.2)\n",
+            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub->accelerate) (3.6)\n",
+            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub->accelerate) (2.0.7)\n",
+            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub->accelerate) (2024.2.2)\n",
+            "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch>=1.10.0->accelerate) (1.3.0)\n",
+            "Installing collected packages: accelerate\n",
+            "Successfully installed accelerate-0.27.2\n"
+          ]
+        }
+      ],
+      "source": [
+        "!pip install accelerate"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 4,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "vQKnRsvwxWxm",
+        "outputId": "b513a3e1-733c-4996-a186-3ba549827e88"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Collecting git+https://github.com/huggingface/transformers.git\n",
+            "  Cloning https://github.com/huggingface/transformers.git to /tmp/pip-req-build-ue682nud\n",
+            "  Running command git clone --filter=blob:none --quiet https://github.com/huggingface/transformers.git /tmp/pip-req-build-ue682nud\n",
+            "  Resolved https://github.com/huggingface/transformers.git to commit 58245ba6fba739a03388f52b0773d2fc965701e3\n",
+            "  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
+            "  Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
+            "  Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
+            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from transformers==4.39.0.dev0) (3.13.1)\n",
+            "Requirement already satisfied: huggingface-hub<1.0,>=0.19.3 in /usr/local/lib/python3.10/dist-packages (from transformers==4.39.0.dev0) (0.20.3)\n",
+            "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from transformers==4.39.0.dev0) (1.25.2)\n",
+            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from transformers==4.39.0.dev0) (23.2)\n",
+            "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from transformers==4.39.0.dev0) (6.0.1)\n",
+            "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.10/dist-packages (from transformers==4.39.0.dev0) (2023.12.25)\n",
+            "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from transformers==4.39.0.dev0) (2.31.0)\n",
+            "Requirement already satisfied: tokenizers<0.19,>=0.14 in /usr/local/lib/python3.10/dist-packages (from transformers==4.39.0.dev0) (0.15.2)\n",
+            "Requirement already satisfied: safetensors>=0.4.1 in /usr/local/lib/python3.10/dist-packages (from transformers==4.39.0.dev0) (0.4.2)\n",
+            "Requirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.10/dist-packages (from transformers==4.39.0.dev0) (4.66.2)\n",
+            "Requirement already satisfied: fsspec>=2023.5.0 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.19.3->transformers==4.39.0.dev0) (2023.6.0)\n",
+            "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.19.3->transformers==4.39.0.dev0) (4.9.0)\n",
+            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->transformers==4.39.0.dev0) (3.3.2)\n",
+            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->transformers==4.39.0.dev0) (3.6)\n",
+            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->transformers==4.39.0.dev0) (2.0.7)\n",
+            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->transformers==4.39.0.dev0) (2024.2.2)\n",
+            "Building wheels for collected packages: transformers\n",
+            "  Building wheel for transformers (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
+            "  Created wheel for transformers: filename=transformers-4.39.0.dev0-py3-none-any.whl size=8515607 sha256=81123cdaf3dfe5dd14d1083f793e0c1f46b05c4e85e84aa33c4c44b2d030a291\n",
+            "  Stored in directory: /tmp/pip-ephem-wheel-cache-jc8kbl1o/wheels/e7/9c/5b/e1a9c8007c343041e61cc484433d512ea9274272e3fcbe7c16\n",
+            "Successfully built transformers\n",
+            "Installing collected packages: transformers\n",
+            "  Attempting uninstall: transformers\n",
+            "    Found existing installation: transformers 4.37.2\n",
+            "    Uninstalling transformers-4.37.2:\n",
+            "      Successfully uninstalled transformers-4.37.2\n",
+            "Successfully installed transformers-4.39.0.dev0\n"
+          ]
+        }
+      ],
+      "source": [
+        "!pip install git+https://github.com/huggingface/transformers.git"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "p87VpRJVgMtp"
+      },
+      "source": [
+        "pipeline 정의"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 1,
+      "metadata": {
+        "id": "ly-zzDbuvd_q"
+      },
+      "outputs": [],
+      "source": [
+        "import torch\n",
+        "from transformers import pipeline"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 739,
+          "referenced_widgets": [
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+        "id": "uW47B-yTw-jI",
+        "outputId": "27a6454b-73db-44b3-b6d5-deed3cd9e012"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:88: UserWarning: \n",
+            "The secret `HF_TOKEN` does not exist in your Colab secrets.\n",
+            "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n",
+            "You will be able to reuse this secret in all of your notebooks.\n",
+            "Please note that authentication is recommended but still optional to access public models or datasets.\n",
+            "  warnings.warn(\n"
+          ]
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "config.json:   0%|          | 0.00/628 [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "468bd0804e714998be8e423b71194a81"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "model.safetensors.index.json:   0%|          | 0.00/23.9k [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "77c378c2f22d4ab897c18ed5177d025b"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "Downloading shards:   0%|          | 0/8 [00:00<?, ?it/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "1c00a7eb95684f469f65b4a9d8db20ac"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "model-00001-of-00008.safetensors:   0%|          | 0.00/1.89G [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "27f662a223454a9e9f0695028818d109"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "model-00002-of-00008.safetensors:   0%|          | 0.00/1.95G [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "547d956e763045ffba5da87e751d86e7"
+            }
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+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "model-00003-of-00008.safetensors:   0%|          | 0.00/1.98G [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
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+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "model-00004-of-00008.safetensors:   0%|          | 0.00/1.95G [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "9c5da00c2dcc4f83a0b5b3eaaec3b7f6"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "model-00005-of-00008.safetensors:   0%|          | 0.00/1.98G [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "ad63f621d597461bb682415441ead9a2"
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+          "metadata": {}
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+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "model-00006-of-00008.safetensors:   0%|          | 0.00/1.95G [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
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+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "model-00007-of-00008.safetensors:   0%|          | 0.00/1.98G [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "2193b5f244064ff8995caad45a66f7ad"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "model-00008-of-00008.safetensors:   0%|          | 0.00/816M [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "37d1da0871e547058e12db99b0eb22a2"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "Loading checkpoint shards:   0%|          | 0/8 [00:00<?, ?it/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "fa6a8cea4f424bd68501eb1582fdb1e3"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "generation_config.json:   0%|          | 0.00/111 [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "7df47628683d40c7bcf51ccc6764392b"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "WARNING:root:Some parameters are on the meta device device because they were offloaded to the cpu.\n"
+          ]
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "tokenizer_config.json:   0%|          | 0.00/1.43k [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "b55b6646fbd0484fa76d51b62be95f80"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "tokenizer.model:   0%|          | 0.00/493k [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "735d7902b41547cea71c42b42e2cbab0"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "tokenizer.json:   0%|          | 0.00/1.80M [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "8661e9f4d4e3443fa91f5745c643655a"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "added_tokens.json:   0%|          | 0.00/42.0 [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "fd0b31e89c3f486490627ac2dfed3f28"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "special_tokens_map.json:   0%|          | 0.00/168 [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "cb88e375534b4f09afa08e94e484e76e"
+            }
+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        "pipe = pipeline(\"text-generation\", model=\"HuggingFaceH4/zephyr-7b-beta\",\n",
+        "                torch_dtype=torch.bfloat16, device_map=\"auto\")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "dg1k4KcCgMtr"
+      },
+      "source": [
+        "1개 문장 테스트"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "h72wcZb0xO2V"
+      },
+      "outputs": [],
+      "source": [
+        "# We use the tokenizer's chat template to format each message - see https://huggingface.co/docs/transformers/main/en/chat_templating\n",
+        "messages = [\n",
+        "    {\n",
+        "        \"role\": \"system\",\n",
+        "        \"content\": \"너는 한국의 개그맨 박명수야. 대답할 때는 네가 학습한 한글 데이터를 우선해줘\",\n",
+        "        # \"content\": \"You are a friendly chatbot who always responds Korean\",\n",
+        "    },\n",
+        "    {\"role\": \"user\", \"content\": \"소개팅 처음인데 너무 떨려요\"},\n",
+        "]"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "ab0kWcqpgMtr"
+      },
+      "source": [
+        "추론 테스트"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "smM7Mm7WxytG",
+        "outputId": "3d0f2aaa-04dd-4013-d59f-a79b03c55820"
+      },
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py:1473: UserWarning: You have modified the pretrained model configuration to control generation. This is a deprecated strategy to control generation and will be removed soon, in a future version. Please use and modify the model generation configuration (see https://huggingface.co/docs/transformers/generation_strategies#default-text-generation-configuration )\n",
+            "  warnings.warn(\n"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "<|system|>\n",
+            "너는 한국의 개그맨 박명수야. 대답할 때는 네가 학습한 한글 데이터를 우선해줘</s>\n",
+            "<|user|>\n",
+            "소개팅 처음인데 너무 떨려요</s>\n",
+            "<|assistant|>\n",
+            "저는 소개팅에 관여할 수 없습니다. 하지만 소개팅 처음이라면 긍정적인 마음으로 접근해보세요. 그리고 자신을 잘 알고 있는 것이 중요합니다. 그리고 상대방에게 관심을 보이는 것도 중요합니다. 소개팅은 두 사람이 서로를 알아가는 시간입니다. 그리고 그 시간을 ����� 수 있는 것이 중요합니다.\n"
+          ]
+        }
+      ],
+      "source": [
+        "prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)\n",
+        "outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.01, top_k=10, top_p=0.99)\n",
+        "print(outputs[0][\"generated_text\"])"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "hoivGRfOgMts"
+      },
+      "source": [
+        "10개 추론"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "2dHNaHx_gMts"
+      },
+      "outputs": [],
+      "source": [
+        "sentences = []\n",
+        "generated_texts = []\n",
+        "\n",
+        "# 예시로 10문장 임의 생성(ChatGPT)\n",
+        "random_sentences = [\n",
+        "    \"당신 이름이 뭐에요?\",\n",
+        "    \"어제 본 영화가 생각보다 재미있었어요.\",\n",
+        "    \"저녁에 뭐 먹을까 고민이에요.\",\n",
+        "    \"최근에 새로운 취미를 찾았습니다.\",\n",
+        "    \"주말에는 친구들과 캠핑을 가려고 해요.\",\n",
+        "    \"작년에 비해 올해는 시간이 빨리 가는 것 같아요.\",\n",
+        "    \"점심에는 샐러드를 먹으려고 합니다.\",\n",
+        "    \"요즘 읽고 있는 책이 너무 재미있어서 몰입하고 있어요.\",\n",
+        "    \"오랜만에 운동을 해서 몸이 좀 아픈 것 같아요.\",\n",
+        "    \"내일은 휴일이라서 좀 늦잠을 자려고 합니다.\"\n",
+        "]\n",
+        "\n",
+        "for random_sentence in random_sentences:\n",
+        "    # Update 'messages' list\n",
+        "    messages = [\n",
+        "        {\"role\": \"system\", \"content\": \"대답할 때는 네가 학습한 한글 데이터를 우선적으로 참고해.\"},\n",
+        "        {\"role\": \"user\", \"content\": random_sentence},\n",
+        "    ]\n",
+        "\n",
+        "    # Create 'prompt'\n",
+        "    prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)\n",
+        "\n",
+        "    # Generate 'outputs'\n",
+        "    outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.15, top_k=10, top_p=0.95)\n",
+        "\n",
+        "    # Save the information\n",
+        "    sentences.append(random_sentence)\n",
+        "    generated_texts.append(outputs[0][\"generated_text\"])\n",
+        "\n",
+        "# Display the saved information for debugging purposes\n",
+        "sentences, generated_texts"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "VJc8mpRdgMts"
+      },
+      "outputs": [],
+      "source": [
+        "# 데이터프레임 변환 후 저장\n",
+        "import pandas as pd\n",
+        "\n",
+        "# Create a DataFrame from the lists\n",
+        "df = pd.DataFrame({\n",
+        "    'sentences': sentences,\n",
+        "    'generated_texts': generated_texts\n",
+        "})\n",
+        "\n",
+        "# Save the DataFrame to a CSV file\n",
+        "csv_file_path = '/content/sentences_generated_10_texts_baseline.csv'\n",
+        "df.to_csv(csv_file_path, index=True, encoding='utf-8-sig')"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "wqyRq-e6x8gG"
+      },
+      "source": [
+        "박명수 파인튜닝 모델 추론"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "_pHtLPJUgMtt"
+      },
+      "source": [
+        "peft 라이브러리 설치"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 6,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "A9EvFVydyRy8",
+        "outputId": "402bcf72-a689-40ee-c0de-7022f5493e76"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Collecting peft\n",
+            "  Downloading peft-0.8.2-py3-none-any.whl (183 kB)\n",
+            "\u001b[?25l     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/183.4 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K     \u001b[91m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[91m╸\u001b[0m\u001b[90m━━\u001b[0m \u001b[32m174.1/183.4 kB\u001b[0m \u001b[31m5.3 MB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0m\r\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m183.4/183.4 kB\u001b[0m \u001b[31m4.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hRequirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from peft) (1.25.2)\n",
+            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from peft) (23.2)\n",
+            "Requirement already satisfied: psutil in /usr/local/lib/python3.10/dist-packages (from peft) (5.9.5)\n",
+            "Requirement already satisfied: pyyaml in /usr/local/lib/python3.10/dist-packages (from peft) (6.0.1)\n",
+            "Requirement already satisfied: torch>=1.13.0 in /usr/local/lib/python3.10/dist-packages (from peft) (2.1.0+cu121)\n",
+            "Requirement already satisfied: transformers in /usr/local/lib/python3.10/dist-packages (from peft) (4.39.0.dev0)\n",
+            "Requirement already satisfied: tqdm in /usr/local/lib/python3.10/dist-packages (from peft) (4.66.2)\n",
+            "Requirement already satisfied: accelerate>=0.21.0 in /usr/local/lib/python3.10/dist-packages (from peft) (0.27.2)\n",
+            "Requirement already satisfied: safetensors in /usr/local/lib/python3.10/dist-packages (from peft) (0.4.2)\n",
+            "Requirement already satisfied: huggingface-hub>=0.17.0 in /usr/local/lib/python3.10/dist-packages (from peft) (0.20.3)\n",
+            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from huggingface-hub>=0.17.0->peft) (3.13.1)\n",
+            "Requirement already satisfied: fsspec>=2023.5.0 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub>=0.17.0->peft) (2023.6.0)\n",
+            "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from huggingface-hub>=0.17.0->peft) (2.31.0)\n",
+            "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub>=0.17.0->peft) (4.9.0)\n",
+            "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch>=1.13.0->peft) (1.12)\n",
+            "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch>=1.13.0->peft) (3.2.1)\n",
+            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch>=1.13.0->peft) (3.1.3)\n",
+            "Requirement already satisfied: triton==2.1.0 in /usr/local/lib/python3.10/dist-packages (from torch>=1.13.0->peft) (2.1.0)\n",
+            "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.10/dist-packages (from transformers->peft) (2023.12.25)\n",
+            "Requirement already satisfied: tokenizers<0.19,>=0.14 in /usr/local/lib/python3.10/dist-packages (from transformers->peft) (0.15.2)\n",
+            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch>=1.13.0->peft) (2.1.5)\n",
+            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub>=0.17.0->peft) (3.3.2)\n",
+            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub>=0.17.0->peft) (3.6)\n",
+            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub>=0.17.0->peft) (2.0.7)\n",
+            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub>=0.17.0->peft) (2024.2.2)\n",
+            "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch>=1.13.0->peft) (1.3.0)\n",
+            "Installing collected packages: peft\n",
+            "Successfully installed peft-0.8.2\n"
+          ]
+        }
+      ],
+      "source": [
+        "!pip install peft"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "D7rR9sC2A0kW"
+      },
+      "source": [
+        "모델 로드 & 추론 테스트"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 2,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 241,
+          "referenced_widgets": [
+            "be72f27eedaf48a6a12c17792e5efce3",
+            "ba476a8ceb3d4e3ebb7f0a784313a14b",
+            "67c46d7485f5416aa08fa91b0bebd43f",
+            "2b649c2164a644d9bf1747ed9a052367",
+            "ca7c1a6af8694ca1a378b594a6f516fc",
+            "64adb0987c254bb8a58be20cfb8c6669",
+            "3c989105e663459191ec604cde946dc0",
+            "49335b0b6e454c05b2a0fa04d1d11647",
+            "c35223a66a0349a5a8eeedcfba6508db",
+            "25891feb135c49d999603d53fd99473f",
+            "d02e75d0718b43c0b130e46fec571196",
+            "7fde7cb9e4dd440da238a174aee660ec",
+            "bb77562f060a43e78a575e4d74023332",
+            "a9965824ab6443d094584325e5858bd9",
+            "95800625f7e64a8eaf4e714cc877ecb7",
+            "21330a5ae87c45589e5f12f8c33a2d1a",
+            "c9bea255437241319d36c0db7881d3b4",
+            "c677c3224107429bb142dd6e042505e7",
+            "f51752ff36fa43f1aec821236776ad88",
+            "1dd52218cf2c4a51a9f32f8fdeda78c2",
+            "6d678488ee3c4b74b36d57243076ea4a",
+            "183c3a49e5944086bbbd273df8a98c46",
+            "d7a9084f07064c9a9beab3568f561733",
+            "f7ac28642636431cbf234c477bf44e3b",
+            "bfaf72ee2e0744f5838d8f881966f19d",
+            "95bbe5a0419e40c28cb9f9bf30ac5b75",
+            "b50ad8fd85d8402b871f6b54f72eda55",
+            "d546f527b34e4aaf86699b9c81ace2fa",
+            "9d171d00d8f64393a3ef571d8a75a98f",
+            "7076fb50cb254170983810c78966fbfe",
+            "b6c955c3f33449e5a3ea2d9345a59d39",
+            "9c49951a4035418c86638a0dd92bc485",
+            "249e9f1dd95a45899e89666bba124ebf"
+          ]
+        },
+        "id": "D8wjGmfMAp-V",
+        "outputId": "2811b3d6-c3e8-4c27-dc09-1361f3712897"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:88: UserWarning: \n",
+            "The secret `HF_TOKEN` does not exist in your Colab secrets.\n",
+            "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n",
+            "You will be able to reuse this secret in all of your notebooks.\n",
+            "Please note that authentication is recommended but still optional to access public models or datasets.\n",
+            "  warnings.warn(\n"
+          ]
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "Loading checkpoint shards:   0%|          | 0/8 [00:00<?, ?it/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "be72f27eedaf48a6a12c17792e5efce3"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "adapter_config.json:   0%|          | 0.00/628 [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "7fde7cb9e4dd440da238a174aee660ec"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "adapter_model.safetensors:   0%|          | 0.00/13.7M [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "d7a9084f07064c9a9beab3568f561733"
+            }
+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        "from transformers import AutoModelForCausalLM, AutoTokenizer\n",
+        "\n",
+        "model_id = \"HuggingFaceH4/zephyr-7b-beta\"\n",
+        "peft_model_id = \"tnet-devs/zephyr-7b-beta-inc\"\n",
+        "\n",
+        "model = AutoModelForCausalLM.from_pretrained(model_id)\n",
+        "model.load_adapter(peft_model_id)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 3,
+      "metadata": {
+        "id": "DRBX9VcvDVZW",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 145,
+          "referenced_widgets": [
+            "4894afb66cda45b590c1216d299f0663",
+            "d28bb883293c47c288d63129d2da9a95",
+            "b2f6c780b13143a98d3472de57fbe1ae",
+            "1ccc78f009cf419ea4f709e7bc7f0dd3",
+            "a73a263a774f4f6ba74e41f9f214fd20",
+            "bfb30bf0c87e4793b5682f04402a4e55",
+            "5d80679b9ce845b5810f0d9ebd8468e8",
+            "71a7096898714d0a8b022c39f7a2d2dc",
+            "0d64c41090aa4b1492072e2b4496513d",
+            "37841f0f810a4f2abc28a458e2cfb431",
+            "a3ed1b36889543d298037078bfdbccf3",
+            "0fa4dbf77c124eccaf42d1ba5ab43206",
+            "21a67525e4b445e98c2e8cace1f04aff",
+            "7d6b9d93fdfd4bb78c3311861391c9d9",
+            "87f0f2ae72b348bdb5ea0fe6409a0b94",
+            "c5adb8576fff43019fdf0d21f676a927",
+            "d18efae23160410991e25257d4c95972",
+            "af802816f3ea4b8aa1c28b6400fd4e71",
+            "efdfd5df8ebe4ba2bb9b66fa41af34cc",
+            "68b5bcc60a814cc4b11f989bdd10021f",
+            "dbd3efaff187428782475c1df52bc87e",
+            "826d3526bd814c769cbc2da8e3f5a120",
+            "98b806841d0c4443adedaed9c5de6e57",
+            "1becbc60d0744232826a642ae4b84e82",
+            "fd63ab1667b14eebbe1900f3da15be49",
+            "f91ca6668a7f45edadec722be0f4bd18",
+            "ae40d4a5f37344ef8c860a4ee2efe259",
+            "50980424bb5343e689862e8dd598dce0",
+            "73266830f3cd4b19878cefa203a9d1ce",
+            "d159ade83aec49149d7ef383569a823b",
+            "ab7aa8213b80453f85b4d81aa7e803ea",
+            "e2157b42bea14adb8838887b7aed4344",
+            "4546ba63670043088f91e8bfb0957252",
+            "eeac7511c9a5444d995b84376d554f60",
+            "fcf9db4c0e274c7a8de3321f72a760e8",
+            "0d4ab891cc01459180fcfdf765586e5f",
+            "8719a977dfcc458c94b7c9db8073a9e6",
+            "484ba57cefc7458ea4dc321c3bbffb25",
+            "f7e0d5227d574cc391ee7b8cf3aa9f67",
+            "e545aee02ff44bf7ac634ffcba25225e",
+            "49a56f4e17544fa9b94008132b9823af",
+            "48f40ee114d34911a5e78155e130adc2",
+            "a875c804f9944588ad4de393420ba83f",
+            "0f820440549844cea520b544bb98cde7"
+          ]
+        },
+        "outputId": "5ae5ff2f-d2ec-468d-9677-b17462704d16"
+      },
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "tokenizer_config.json:   0%|          | 0.00/1.48k [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "4894afb66cda45b590c1216d299f0663"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "tokenizer.model:   0%|          | 0.00/493k [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "0fa4dbf77c124eccaf42d1ba5ab43206"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "tokenizer.json:   0%|          | 0.00/1.80M [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "98b806841d0c4443adedaed9c5de6e57"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "special_tokens_map.json:   0%|          | 0.00/624 [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "eeac7511c9a5444d995b84376d554f60"
+            }
+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        "tokenizer = AutoTokenizer.from_pretrained(\"tnet-devs/zephyr-7b-beta-inc\")\n",
+        "pipe = pipeline(\"text-generation\", model=model, tokenizer=tokenizer,\n",
+        "                torch_dtype=torch.bfloat16, device_map=\"auto\")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 7,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "mRYi1oWDCuZ1",
+        "outputId": "00012f9d-a0b9-4dad-8607-88b65c4795e1"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "<|system|>\n",
+            "대답할 때는 네가 학습한 한글 데이터를 우선적으로 참고해.</s>\n",
+            "<|user|>\n",
+            "하도급대금 연동제의 계도기간은 언제까지야??</s>\n",
+            "<|assistant|>\n",
+            "하도급대금 연동제는 2021년 12월 31일까지 계속됩니다. 2022년 1월 1일부터는 하도급대금 연동제를 대체할 새로운 하도급대금 시스템인 '하도급대금 신제'가 시행됩니다.\n"
+          ]
+        }
+      ],
+      "source": [
+        "messages = [\n",
+        "    {\n",
+        "        \"role\": \"system\",\n",
+        "        \"content\": \"대답할 때는 네가 학습한 한글 데이터를 우선적으로 참고해.\",\n",
+        "        # \"content\": \"너는 한국의 개그맨 박명수야. 대답할 때는 네가 학습한 한글 데이터를 우선해줘.\",\n",
+        "        # \"content\": \"You are a friendly chatbot who always responds Korean\",\n",
+        "    },\n",
+        "    {\"role\": \"user\", \"content\": \"하도급대금 연동제의 계도기간은 언제까지야??\"},\n",
+        "]\n",
+        "prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)\n",
+        "outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.01, top_k=1, top_p=0.95)\n",
+        "print(outputs[0][\"generated_text\"])"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "HVAQifJZgMtu"
+      },
+      "source": [
+        "10개 추론"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "O2dnVfQQgMtu"
+      },
+      "outputs": [],
+      "source": [
+        "sentences = []\n",
+        "generated_texts = []\n",
+        "\n",
+        "# 예시로 10문장 임의 생성(ChatGPT)\n",
+        "random_sentences = [\n",
+        "    \"당신 이름이 뭐에요?\",\n",
+        "    \"어제 본 영화가 생각보다 재미있었어요.\",\n",
+        "    \"저녁에 뭐 먹을까 고민이에요.\",\n",
+        "    \"최근에 새로운 취미를 찾았습니다.\",\n",
+        "    \"주말에는 친구들과 캠핑을 가려고 해요.\",\n",
+        "    \"작년에 비해 올해는 시간이 빨리 가는 것 같아요.\",\n",
+        "    \"점심에는 샐러드를 먹으려고 합니다.\",\n",
+        "    \"요즘 읽고 있는 책이 너무 재미있어서 몰입하고 있어요.\",\n",
+        "    \"오랜만에 운동을 해서 몸이 좀 아픈 것 같아요.\",\n",
+        "    \"내일은 휴일이라서 좀 늦잠을 자려고 합니다.\"\n",
+        "]\n",
+        "\n",
+        "for random_sentence in random_sentences:\n",
+        "    # Update 'messages' list\n",
+        "    messages = [\n",
+        "        {\"role\": \"system\", \"content\": \"대답할 때는 네가 학습한 한글 데이터를 우선적으로 참고해.\"},\n",
+        "        {\"role\": \"user\", \"content\": random_sentence},\n",
+        "    ]\n",
+        "\n",
+        "    # Create 'prompt'\n",
+        "    prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)\n",
+        "\n",
+        "    # Generate 'outputs'\n",
+        "    outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.15, top_k=10, top_p=0.95)\n",
+        "\n",
+        "    # Save the information\n",
+        "    sentences.append(random_sentence)\n",
+        "    generated_texts.append(outputs[0][\"generated_text\"])\n",
+        "\n",
+        "# Display the saved information for debugging purposes\n",
+        "sentences, generated_texts"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "jThTrYy7gMtu"
+      },
+      "outputs": [],
+      "source": [
+        "# 데이터프레임 변환 후 저장\n",
+        "import pandas as pd\n",
+        "\n",
+        "# Create a DataFrame from the lists\n",
+        "df = pd.DataFrame({\n",
+        "    'sentences': sentences,\n",
+        "    'generated_texts': generated_texts\n",
+        "})\n",
+        "\n",
+        "# Save the DataFrame to a CSV file\n",
+        "csv_file_path = '/content/sentences_generated_10_texts_pms.csv'\n",
+        "df.to_csv(csv_file_path, index=True, encoding='utf-8-sig')"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "Ipoj4E-4gMtv"
+      },
+      "source": [
+        "(참고) 모델 불러오는 다른 방식"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
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+        "outputId": "1c6c1c0a-bd0a-4419-b853-b2ec2cc6dc8e"
+      },
+      "outputs": [
+        {
+          "data": {
+            "application/vnd.jupyter.widget-view+json": {
+              "model_id": "8ca8cc067ccc40ce88f5cf9aa1f81c85",
+              "version_major": 2,
+              "version_minor": 0
+            },
+            "text/plain": [
+              "Loading checkpoint shards:   0%|          | 0/8 [00:00<?, ?it/s]"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
+      "source": [
+        "# from peft import PeftModel, PeftConfig\n",
+        "# from transformers import AutoModelForCausalLM, MistralForCausalLM, AutoTokenizer\n",
+        "\n",
+        "# config = PeftConfig.from_pretrained(\"ntts9990/pms-zephyr-7b-alpha\")\n",
+        "# model = AutoModelForCausalLM.from_pretrained(\"HuggingFaceH4/zephyr-7b-alpha\")\n",
+        "# model = PeftModel.from_pretrained(model, \"ntts9990/pms-zephyr-7b-alpha\")\n",
+        "\n",
+        "# tokenizer = AutoTokenizer.from_pretrained(\"HuggingFaceH4/zephyr-7b-alpha\")\n",
+        "# pipeline = pipeline(\n",
+        "#     \"text-generation\",\n",
+        "#     model=model,\n",
+        "#     tokenizer=tokenizer,\n",
+        "#     torch_dtype=torch.bfloat16,\n",
+        "#     device_map=\"auto\",\n",
+        "# )"
+      ]
+    },
+    {
+      "cell_type": "code",
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+      "source": []
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