diff --git a/README.md b/README.md
index fb187e0b..54775a50 100644
--- a/README.md
+++ b/README.md
@@ -32,6 +32,7 @@ Disclaimer: Examples contributed by the community and partners do not represent
 | [function_calling.ipynb](mistral/function_calling/function_calling.ipynb)      | function calling             | Use Mistral API for function calling                                             |
 | [evaluation.ipynb](mistral/evaluation/evaluation.ipynb)                        | evaluation                   | Evaluate models with Mistral API                                                 |
 | [mistral_finetune_api.ipynb](mistral/fine_tune/mistral_finetune_api.ipynb)     | fine-tuning                  | Finetune a model with Mistral fine-tuning API                                    |
+| [codestral_cobol_finetuning.ipynb](mistral/fine_tune/codestral_cobol_finetuning.ipynb)     | fine-tuning                  | Finetune Codestral on Cobol public repository                                   |
 | [mistral-search-engine.ipynb](mistral/rag/mistral-search-engine.ipynb)         | RAG, function calling        | Search engine built with Mistral API, function calling and RAG                   |
 | [prefix_use_cases.ipynb](mistral/prompting/prefix_use_cases.ipynb)             | prefix, prompting            | Cool examples with Mistral's prefix feature                                      |
 | [synthetic_data_gen_and_finetune.ipynb](mistral/data_generation/synthetic_data_gen_and_finetune.ipynb) | data generation, fine-tuning | Simple data generation and fine-tuning guide        |
diff --git a/mistral/fine_tune/codestral_cobol_finetuning.ipynb b/mistral/fine_tune/codestral_cobol_finetuning.ipynb
new file mode 100644
index 00000000..99fdc06f
--- /dev/null
+++ b/mistral/fine_tune/codestral_cobol_finetuning.ipynb
@@ -0,0 +1,1145 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "84cb7587-aa4f-4c2e-99c0-426bb58c33c8",
+   "metadata": {},
+   "source": [
+    "# Assessing finetuning impact on Cobol repository "
+   ]
+  },
+  {
+   "attachments": {
+    "3cbafa57-5784-4842-b774-0f6ec9a6f7a4.png": {
+     "image/png": 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"
+    }
+   },
+   "cell_type": "markdown",
+   "id": "d311fa6a-b828-4dbd-a095-5705757b6368",
+   "metadata": {},
+   "source": [
+    "![image.png](attachment:3cbafa57-5784-4842-b774-0f6ec9a6f7a4.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "eb301e71-56d6-443c-8c42-dab9eca9c272",
+   "metadata": {},
+   "source": [
+    "## Import needed packages\n",
+    "\n",
+    "The first step is to install the needed packages `mistralai` and import the needed packages : "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "40f271c9-49ce-4971-9d71-4cc538054117",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Requirement already satisfied: mistralai in /opt/miniconda3/envs/mistral_2/lib/python3.8/site-packages (1.1.0)\n",
+      "Requirement already satisfied: eval-type-backport<0.3.0,>=0.2.0 in /opt/miniconda3/envs/mistral_2/lib/python3.8/site-packages (from mistralai) (0.2.0)\n",
+      "Requirement already satisfied: httpx<0.28.0,>=0.27.0 in /opt/miniconda3/envs/mistral_2/lib/python3.8/site-packages (from mistralai) (0.27.2)\n",
+      "Requirement already satisfied: jsonpath-python<2.0.0,>=1.0.6 in /opt/miniconda3/envs/mistral_2/lib/python3.8/site-packages (from mistralai) (1.0.6)\n",
+      "Requirement already satisfied: pydantic<3.0.0,>=2.9.0 in /opt/miniconda3/envs/mistral_2/lib/python3.8/site-packages (from mistralai) (2.9.2)\n",
+      "Requirement already satisfied: python-dateutil==2.8.2 in /opt/miniconda3/envs/mistral_2/lib/python3.8/site-packages (from mistralai) (2.8.2)\n",
+      "Requirement already satisfied: typing-inspect<0.10.0,>=0.9.0 in /opt/miniconda3/envs/mistral_2/lib/python3.8/site-packages (from mistralai) (0.9.0)\n",
+      "Requirement already satisfied: six>=1.5 in /opt/miniconda3/envs/mistral_2/lib/python3.8/site-packages (from python-dateutil==2.8.2->mistralai) (1.16.0)\n",
+      "Requirement already satisfied: anyio in /opt/miniconda3/envs/mistral_2/lib/python3.8/site-packages (from httpx<0.28.0,>=0.27.0->mistralai) (4.4.0)\n",
+      "Requirement already satisfied: certifi in /opt/miniconda3/envs/mistral_2/lib/python3.8/site-packages (from httpx<0.28.0,>=0.27.0->mistralai) (2024.7.4)\n",
+      "Requirement already satisfied: httpcore==1.* in /opt/miniconda3/envs/mistral_2/lib/python3.8/site-packages (from httpx<0.28.0,>=0.27.0->mistralai) (1.0.5)\n",
+      "Requirement already satisfied: idna in /opt/miniconda3/envs/mistral_2/lib/python3.8/site-packages (from httpx<0.28.0,>=0.27.0->mistralai) (3.8)\n",
+      "Requirement already satisfied: sniffio in /opt/miniconda3/envs/mistral_2/lib/python3.8/site-packages (from httpx<0.28.0,>=0.27.0->mistralai) (1.3.1)\n",
+      "Requirement already satisfied: h11<0.15,>=0.13 in /opt/miniconda3/envs/mistral_2/lib/python3.8/site-packages (from httpcore==1.*->httpx<0.28.0,>=0.27.0->mistralai) (0.14.0)\n",
+      "Requirement already satisfied: annotated-types>=0.6.0 in /opt/miniconda3/envs/mistral_2/lib/python3.8/site-packages (from pydantic<3.0.0,>=2.9.0->mistralai) (0.7.0)\n",
+      "Requirement already satisfied: pydantic-core==2.23.4 in /opt/miniconda3/envs/mistral_2/lib/python3.8/site-packages (from pydantic<3.0.0,>=2.9.0->mistralai) (2.23.4)\n",
+      "Requirement already satisfied: typing-extensions>=4.6.1 in /opt/miniconda3/envs/mistral_2/lib/python3.8/site-packages (from pydantic<3.0.0,>=2.9.0->mistralai) (4.11.0)\n",
+      "Requirement already satisfied: mypy-extensions>=0.3.0 in /opt/miniconda3/envs/mistral_2/lib/python3.8/site-packages (from typing-inspect<0.10.0,>=0.9.0->mistralai) (1.0.0)\n",
+      "Requirement already satisfied: exceptiongroup>=1.0.2 in /opt/miniconda3/envs/mistral_2/lib/python3.8/site-packages (from anyio->httpx<0.28.0,>=0.27.0->mistralai) (1.2.2)\n"
+     ]
+    }
+   ],
+   "source": [
+    "! pip install mistralai"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "3df2bae6-6559-4b14-a436-abdb2cc7161e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from mistralai import Mistral\n",
+    "from getpass import getpass\n",
+    "import os\n",
+    "import numpy as np\n",
+    "import time\n",
+    "import math\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "attachments": {
+    "89bb8a49-5c19-4197-9ecc-e63e4e428405.png": {
+     "image/png": 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"
+    }
+   },
+   "cell_type": "markdown",
+   "id": "f704b5f5-f576-4ba7-ae2c-49ad0898e6b1",
+   "metadata": {},
+   "source": [
+    "# Step 1 : Access Mistral client and get your Github token\n",
+    "\n",
+    "To access programatically to a Github repo you want to finetune you must generate a github Fine-grained token. \n",
+    "Generate your token in the `Settings/Developer Settings` of your Github profile. \n",
+    "\n",
+    "![image.png](attachment:89bb8a49-5c19-4197-9ecc-e63e4e428405.png)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "2676ec49-82cc-447f-975c-801fd5879ae8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "api_key= getpass(\"Type your API Key\")\n",
+    "github_token =  getpass(\"Type your Github token\")\n",
+    "\n",
+    "client = Mistral(api_key=api_key)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7145c7c0-86d2-4abe-89e6-e08f4771fbcb",
+   "metadata": {},
+   "source": [
+    "# Step 2 : Finetune Codestral on a Cobol repository  \n",
+    "\n",
+    "For the sake of this experiment we will be finetuning Codestral on an open-source [Cobol course](https://github.com/openmainframeproject/cobol-programming-course/tree/master/COBOL%20Programming%20Course%20%232%20-%20Learning%20COBOL) This repository is specialised in Cobol.\n",
+    "Finetuning a Codestral model on [Cobol course](https://github.com/openmainframeproject/cobol-programming-course/tree/master/COBOL%20Programming%20Course%20%232%20-%20Learning%20COBOL) is very straightforward."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "a2df5d90-e7b8-4399-a785-91eea67c4c77",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "created_jobs = client.fine_tuning.jobs.create(\n",
+    "    model=\"codestral-latest\",\n",
+    "    auto_start=True,\n",
+    "    repositories=[\n",
+    "        {\n",
+    "            \"type\": \"github\",\n",
+    "            \"owner\": \"openmainframeproject\",\n",
+    "            \"name\": \"cobol-programming-course\",\n",
+    "            \"token\":github_token\n",
+    "        }\n",
+    "    ],\n",
+    "    hyperparameters={\n",
+    "        \"training_steps\": 50,\n",
+    "        \"learning_rate\":0.0001\n",
+    "    }\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "676a8eef-914c-42d2-975b-27b707ad3548",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "ft:codestral-latest:9fd0b0bc:20241120:fff88efd\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Extract step_number and train_loss from the job data\n",
+    "retrieved_job = client.fine_tuning.jobs.get(job_id = created_jobs.id)\n",
+    "print(retrieved_job.fine_tuned_model)\n",
+    "step_numbers = [checkpoint.step_number for checkpoint in retrieved_job.checkpoints]\n",
+    "train_losses = [checkpoint.metrics.train_loss for checkpoint in retrieved_job.checkpoints]\n",
+    "\n",
+    "# Plot the data\n",
+    "plt.figure(figsize=(12, 8))\n",
+    "plt.plot(step_numbers, train_losses, marker='o', linestyle='-', color='b', label='Train Loss')\n",
+    "\n",
+    "# Adding titles and labels\n",
+    "plt.title('Finetune Codestral on your repo - Train Loss', fontsize=16, fontweight='bold')\n",
+    "plt.xlabel('Step Number', fontsize=14)\n",
+    "plt.ylabel('Train Loss', fontsize=14)\n",
+    "\n",
+    "# Adding grid for better readability\n",
+    "plt.grid(True, linestyle='--', alpha=0.7)\n",
+    "\n",
+    "# Adding legend\n",
+    "plt.legend(loc='best')\n",
+    "\n",
+    "# Customizing the appearance\n",
+    "plt.xticks(fontsize=12)\n",
+    "plt.yticks(fontsize=12)\n",
+    "\n",
+    "# Adding a background color\n",
+    "plt.gca().set_facecolor('#f0f0f0')\n",
+    "\n",
+    "# Display the plot\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "978f6802-df7c-4555-8810-81f470fec023",
+   "metadata": {},
+   "source": [
+    "# Step 3 : Model Performance Evaluation\n",
+    "\n",
+    "The logic of evaluation in this code is based on next line accuracy between the model's generated suggestion and the actual answer.\n",
+    "\n",
+    "Our goal is to evaluate the performance of two models: Codestral and Codestral finetuned on a COBOL repository. The performances are tested on three different files to assess the models' capabilities and potential overfitting. The files used for testing are:\n",
+    "\n",
+    "1. **COBOL File from Finetuned Repo**: This file is taken from the repository on which Codestral was finetuned.\n",
+    "2. **New COBOL File**: A new file that is not taken from the repository on which Codestral was finetuned.\n",
+    "3. **Testimony Python File**: A Python file that the models have not seen before, providing a measure of the models' ability to generalize to a different programming language."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b1489abd-bdeb-4141-8875-c810b4119643",
+   "metadata": {},
+   "source": [
+    "### Step 3.1 Format evaluation dataset "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "922c58c5-76e8-4697-bc01-bfd8689f6c67",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def generate_fim_sample(sample, rng):\n",
+    "    \"\"\"\n",
+    "    Generate a FIM sample from a code sample.\n",
+    "    \"\"\"\n",
+    "    # Split lines and remove empty lines\n",
+    "    lines = [line for line in sample.split(\"\\n\") if line.strip() != \"\"]\n",
+    "    reduced_sample = \"\\n\".join(lines)\n",
+    "    assert len(lines) >= 2, f\"{len(lines)} {sample}\"\n",
+    "\n",
+    "    # Randomly select a line\n",
+    "    line = rng.integers(1, len(lines))\n",
+    "    assert 1 <= line < len(lines), f\"{line} {len(lines)}\"\n",
+    "\n",
+    "    # Prefix, suffix, answer\n",
+    "    prefix = \"\\n\".join(lines[:line]) + \"\\n\"\n",
+    "    answer = lines[line]\n",
+    "    suffix = \"\\n\".join(lines[line + 1:])\n",
+    "\n",
+    "    if len(suffix) > 0:\n",
+    "        answer += \"\\n\"\n",
+    "\n",
+    "    assert (len(suffix) == 0) or (suffix[0] != \"\\n\"), f\"{suffix}\"\n",
+    "    assert (len(suffix) == 0) or answer.endswith(\"\\n\"), answer\n",
+    "\n",
+    "    assert (\n",
+    "        prefix + answer + suffix == reduced_sample\n",
+    "    ), f\"\\nPrefix-Answer-Suffix\\n{prefix}{answer}{suffix}\\nSample\\n{reduced_sample}\"\n",
+    "\n",
+    "    return prefix, suffix, answer\n",
+    "\n",
+    "def generate_fim_examples(sample, max_num_examples, rng):\n",
+    "    \"\"\"\n",
+    "    Generates deduplicated FIM examples.\n",
+    "    \"\"\"\n",
+    "    # Generate a set of unique FIM samples\n",
+    "    deduplicated = {generate_fim_sample(sample, rng) for _ in range(max_num_examples)}\n",
+    "\n",
+    "    # Convert the set of tuples to a list of dictionaries\n",
+    "    examples = [{\"prefix\": example[0], \"answer\": example[2], \"suffix\": example[1]} for example in deduplicated]\n",
+    "\n",
+    "    return examples"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "4432b983-bbfd-4d0f-afa4-0493f4fb66e1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "KNOWN_COBOL_FILE=\"\"\"\n",
+    " *-----------------------\n",
+    "      * Copyright Contributors to the COBOL Programming Course\n",
+    "      * SPDX-License-Identifier: CC-BY-4.0\n",
+    "      *-----------------------\n",
+    "       IDENTIFICATION DIVISION.\n",
+    "      *-----------------------\n",
+    "       PROGRAM-ID.    CBLDB23\n",
+    "       AUTHOR.        Otto B. Relational\n",
+    "\n",
+    "       ENVIRONMENT DIVISION.\n",
+    "      *--------------------\n",
+    "       CONFIGURATION SECTION.\n",
+    "       INPUT-OUTPUT SECTION.\n",
+    "       FILE-CONTROL.\n",
+    "           SELECT REPOUT\n",
+    "                  ASSIGN TO UT-S-REPORT.\n",
+    "           SELECT CARDIN\n",
+    "                  ASSIGN TO DA-S-CARDIN.\n",
+    "\n",
+    "       DATA DIVISION.\n",
+    "      *-------------\n",
+    "       FILE SECTION.\n",
+    "       FD  REPOUT\n",
+    "               RECORD CONTAINS 120 CHARACTERS\n",
+    "               LABEL RECORDS ARE OMITTED\n",
+    "               RECORDING MODE F\n",
+    "               DATA RECORD IS REPREC.\n",
+    "       01  REPREC.\n",
+    "           05  ACCT-NO-O      PIC X(8).\n",
+    "           05  ACCT-LASTN-O   PIC X(20).\n",
+    "           05  ACCT-FIRSTN-O  PIC X(15).\n",
+    "           05  ACCT-ADDR3-O   PIC X(15).\n",
+    "       FD      CARDIN\n",
+    "               RECORD CONTAINS 80 CHARACTERS\n",
+    "               BLOCK CONTAINS 0 RECORDS\n",
+    "               RECORDING MODE F\n",
+    "               LABEL RECORDS ARE OMITTED.\n",
+    "       01  CARDREC                    PIC X(80).\n",
+    "\n",
+    "       WORKING-STORAGE SECTION.\n",
+    "      *****************************************************\n",
+    "      * STRUCTURE FOR INPUT                               *\n",
+    "      *****************************************************\n",
+    "       01  IOAREA.\n",
+    "               02  STATE              PIC X(25).\n",
+    "               02  FILLER             PIC X(55).\n",
+    "       77  INPUT-SWITCH        PIC X          VALUE  'Y'.\n",
+    "               88  NOMORE-INPUT               VALUE  'N'.\n",
+    "      *****************************************************\n",
+    "      * SQL INCLUDE FOR SQLCA                             *\n",
+    "      *****************************************************\n",
+    "                EXEC SQL INCLUDE SQLCA  END-EXEC.\n",
+    "      *****************************************************\n",
+    "      * DECLARATIONS FOR SQL ERROR HANDLING               *\n",
+    "      *****************************************************\n",
+    "       01 ERROR-MESSAGE.\n",
+    "           02 ERROR-LEN      PIC S9(4)  COMP VALUE +1320.\n",
+    "           02 ERROR-TEXT     PIC X(132) OCCURS 10 TIMES\n",
+    "                                        INDEXED BY ERROR-INDEX.\n",
+    "       77 ERROR-TEXT-LEN     PIC S9(9)  COMP VALUE +132.\n",
+    "       77 ERROR-TEXT-HBOUND  PIC S9(9)  COMP VALUE +10.\n",
+    "      * USER DEFINED ERROR MESSAGE\n",
+    "       01 UD-ERROR-MESSAGE   PIC X(80)  VALUE SPACES.\n",
+    "      *****************************************************\n",
+    "      * SQL DECLARATION FOR VIEW ACCOUNTS                 *\n",
+    "      *****************************************************\n",
+    "                EXEC SQL DECLARE Z#####T TABLE\n",
+    "                        (ACCTNO     CHAR(8)  NOT NULL,\n",
+    "                         LIMIT      DECIMAL(9,2)     ,\n",
+    "                         BALANCE    DECIMAL(9,2)     ,\n",
+    "                         SURNAME    CHAR(20) NOT NULL,\n",
+    "                         FIRSTN     CHAR(15) NOT NULL,\n",
+    "                         ADDRESS1   CHAR(25) NOT NULL,\n",
+    "                         ADDRESS2   CHAR(20) NOT NULL,\n",
+    "                         ADDRESS3   CHAR(15) NOT NULL,\n",
+    "                         RESERVED   CHAR(7)  NOT NULL,\n",
+    "                         COMMENTS   CHAR(50) NOT NULL)\n",
+    "                         END-EXEC.\n",
+    "      *****************************************************\n",
+    "      * SQL CURSORS                                       *\n",
+    "      *****************************************************\n",
+    "                EXEC SQL DECLARE CUR1  CURSOR FOR\n",
+    "                         SELECT * FROM Z#####T\n",
+    "                     END-EXEC.\n",
+    "                EXEC SQL DECLARE CUR2  CURSOR FOR\n",
+    "                         SELECT *\n",
+    "                         FROM   Z#####T\n",
+    "                         WHERE  ADDRESS3 = :STATE\n",
+    "                      END-EXEC.\n",
+    "      *****************************************************\n",
+    "      * STRUCTURE FOR CUSTOMER RECORD                     *\n",
+    "      *****************************************************\n",
+    "       01 CUSTOMER-RECORD.\n",
+    "          02 ACCT-NO            PIC X(8).\n",
+    "          02 ACCT-LIMIT         PIC S9(7)V99 COMP-3.\n",
+    "          02 ACCT-BALANCE       PIC S9(7)V99 COMP-3.\n",
+    "          02 ACCT-LASTN         PIC X(20).\n",
+    "          02 ACCT-FIRSTN        PIC X(15).\n",
+    "          02 ACCT-ADDR1         PIC X(25).\n",
+    "          02 ACCT-ADDR2         PIC X(20).\n",
+    "          02 ACCT-ADDR3         PIC X(15).\n",
+    "          02 ACCT-RSRVD         PIC X(7).\n",
+    "          02 ACCT-COMMENT       PIC X(50).\n",
+    "\n",
+    "       PROCEDURE DIVISION.\n",
+    "      *------------------\n",
+    "       PROG-START.\n",
+    "                OPEN INPUT  CARDIN.\n",
+    "                OPEN OUTPUT REPOUT.\n",
+    "                READ CARDIN RECORD INTO IOAREA\n",
+    "                   AT END SET NOMORE-INPUT TO TRUE.\n",
+    "                PERFORM PROCESS-INPUT\n",
+    "                   UNTIL NOMORE-INPUT.\n",
+    "       PROG-END.\n",
+    "                CLOSE CARDIN\n",
+    "                      REPOUT.\n",
+    "                GOBACK.\n",
+    "       PROCESS-INPUT.\n",
+    "                IF STATE = '*'\n",
+    "                   PERFORM GET-ALL\n",
+    "                ELSE\n",
+    "                   PERFORM GET-SPECIFIC.\n",
+    "                READ CARDIN RECORD INTO IOAREA\n",
+    "                   AT END SET NOMORE-INPUT TO TRUE.\n",
+    "       GET-ALL.\n",
+    "                EXEC SQL OPEN CUR1  END-EXEC.\n",
+    "                IF SQLCODE NOT = 0 THEN\n",
+    "                   MOVE 'OPEN CUR1' TO UD-ERROR-MESSAGE\n",
+    "                   PERFORM SQL-ERROR-HANDLING\n",
+    "                END-IF\n",
+    "                EXEC SQL FETCH CUR1  INTO :CUSTOMER-RECORD END-EXEC.\n",
+    "                PERFORM PRINT-ALL\n",
+    "                     UNTIL SQLCODE IS NOT EQUAL TO ZERO.\n",
+    "                IF SQLCODE NOT = 100 THEN\n",
+    "                   MOVE 'FETCH CUR1' TO UD-ERROR-MESSAGE\n",
+    "                   PERFORM SQL-ERROR-HANDLING\n",
+    "                END-IF\n",
+    "                EXEC SQL CLOSE CUR1  END-EXEC.\n",
+    "                IF SQLCODE NOT = 0 THEN\n",
+    "                   MOVE 'CLOSE CUR1' TO UD-ERROR-MESSAGE\n",
+    "                   PERFORM SQL-ERROR-HANDLING\n",
+    "                END-IF\n",
+    "                .\n",
+    "       PRINT-ALL.\n",
+    "                PERFORM PRINT-A-LINE.\n",
+    "                EXEC SQL FETCH CUR1  INTO :CUSTOMER-RECORD END-EXEC.\n",
+    "       GET-SPECIFIC.\n",
+    "                EXEC SQL OPEN  CUR2  END-EXEC.\n",
+    "                IF SQLCODE NOT = 0 THEN\n",
+    "                   MOVE 'OPEN CUR2' TO UD-ERROR-MESSAGE\n",
+    "                   PERFORM SQL-ERROR-HANDLING\n",
+    "                END-IF\n",
+    "                EXEC SQL FETCH CUR2  INTO :CUSTOMER-RECORD END-EXEC.\n",
+    "                PERFORM PRINT-SPECIFIC\n",
+    "                     UNTIL SQLCODE IS NOT EQUAL TO ZERO.\n",
+    "                IF SQLCODE NOT = 100 THEN\n",
+    "                   MOVE 'FETCH CUR2' TO UD-ERROR-MESSAGE\n",
+    "                   PERFORM SQL-ERROR-HANDLING\n",
+    "                END-IF\n",
+    "                EXEC SQL CLOSE CUR2  END-EXEC.\n",
+    "                IF SQLCODE NOT = 0 THEN\n",
+    "                   MOVE 'CLOSE CUR2' TO UD-ERROR-MESSAGE\n",
+    "                   PERFORM SQL-ERROR-HANDLING\n",
+    "                END-IF\n",
+    "                .\n",
+    "       PRINT-SPECIFIC.\n",
+    "                PERFORM PRINT-A-LINE.\n",
+    "                EXEC SQL FETCH CUR2  INTO :CUSTOMER-RECORD END-EXEC.\n",
+    "       PRINT-A-LINE.\n",
+    "                MOVE  ACCT-NO      TO  ACCT-NO-O.\n",
+    "                MOVE  ACCT-LASTN   TO  ACCT-LASTN-O.\n",
+    "                MOVE  ACCT-FIRSTN  TO  ACCT-FIRSTN-O.\n",
+    "                MOVE  ACCT-ADDR3   TO  ACCT-ADDR3-O.\n",
+    "                WRITE REPREC AFTER ADVANCING 2 LINES.\n",
+    "\n",
+    "       SQL-ERROR-HANDLING.\n",
+    "           DISPLAY 'ERROR AT ' FUNCTION TRIM(UD-ERROR-MESSAGE, TRAILING)\n",
+    "           CALL 'DSNTIAR' USING SQLCA ERROR-MESSAGE ERROR-TEXT-LEN.\n",
+    "           PERFORM VARYING ERROR-INDEX FROM 1 BY 1\n",
+    "                     UNTIL ERROR-INDEX > ERROR-TEXT-HBOUND\n",
+    "                        OR ERROR-TEXT(ERROR-INDEX) = SPACES\n",
+    "              DISPLAY FUNCTION TRIM(ERROR-TEXT(ERROR-INDEX), TRAILING)\n",
+    "           END-PERFORM\n",
+    "           IF SQLCODE NOT = 0 AND SQLCODE NOT = 100\n",
+    "              MOVE 1000 TO RETURN-CODE\n",
+    "              STOP RUN\n",
+    "           END-IF\n",
+    "           .\n",
+    "\"\"\"\n",
+    "\n",
+    "NEW_COBOL_FILE = \"\"\"\"\n",
+    "       identification division.\n",
+    "       program-id. merge-sort-example.\n",
+    "\n",
+    "       environment division.\n",
+    "       input-output section.\n",
+    "\n",
+    "       file-control.\n",
+    "\n",
+    "           select fd-test-file-1 assign to \"test-file-1.txt\"\n",
+    "           organization is line sequential\n",
+    "           file status is ws-fs-status-1.\n",
+    "\n",
+    "           select fd-test-file-2 assign to \"test-file-2.txt\"\n",
+    "           organization is line sequential\n",
+    "           file status is ws-fs-status-2.\n",
+    "\n",
+    "           select fd-sorting-file assign to \"work-temp.txt\".\n",
+    "\n",
+    "           select fd-merged-file assign to \"merge-output.txt\"\n",
+    "           organization is line sequential\n",
+    "           file status is ws-fs-status-merge.\n",
+    "\n",
+    "           select fd-sorted-contract-id\n",
+    "           assign to \"sorted-contract-id.txt\"\n",
+    "           organization is line sequential\n",
+    "           file status is ws-fs-status-sorted.\n",
+    "\n",
+    "\n",
+    "       data division.\n",
+    "\n",
+    "       file section.\n",
+    "\n",
+    "       sd  fd-sorting-file.\n",
+    "       01  f-customer-record-sort.\n",
+    "           05  f-customer-id                       pic 9(5).\n",
+    "           05  f-customer-last-name                pic x(50).\n",
+    "           05  f-customer-first-name               pic x(50).\n",
+    "           05  f-customer-contract-id              pic 9(5).\n",
+    "           05  f-customer-comment                  pic x(25).\n",
+    "\n",
+    "       fd  fd-test-file-1 recording mode F.\n",
+    "       01  f-customer-record-east.\n",
+    "           05  f-customer-id                       pic 9(5).\n",
+    "           05  f-customer-last-name                pic x(50).\n",
+    "           05  f-customer-first-name               pic x(50).\n",
+    "           05  f-customer-contract-id              pic 9(5).\n",
+    "           05  f-customer-comment                  pic x(25).\n",
+    "\n",
+    "       fd  fd-test-file-2 recording mode F.\n",
+    "       01  f-customer-record-west.\n",
+    "           05  f-customer-id                       pic 9(5).\n",
+    "           05  f-customer-last-name                pic x(50).\n",
+    "           05  f-customer-first-name               pic x(50).\n",
+    "           05  f-customer-contract-id              pic 9(5).\n",
+    "           05  f-customer-comment                  pic x(25).\n",
+    "\n",
+    "       fd  fd-merged-file recording mode F.\n",
+    "       01  f-customer-record-merged.\n",
+    "           05  f-customer-id                       pic 9(5).\n",
+    "           05  f-customer-last-name                pic x(50).\n",
+    "           05  f-customer-first-name               pic x(50).\n",
+    "           05  f-customer-contract-id              pic 9(5).\n",
+    "           05  f-customer-comment                  pic x(25).\n",
+    "\n",
+    "       fd  fd-sorted-contract-id recording mode F.\n",
+    "       01  f-customer-record-sorted-contract-id.\n",
+    "           05  f-customer-id                       pic 9(5).\n",
+    "           05  f-customer-last-name                pic x(50).\n",
+    "           05  f-customer-first-name               pic x(50).\n",
+    "           05  f-customer-contract-id              pic 9(5).\n",
+    "           05  f-customer-comment                  pic x(25).\n",
+    "\n",
+    "       working-storage section.\n",
+    "\n",
+    "       01  ws-fs-status-1                          pic xx.\n",
+    "       01  ws-fs-status-2                          pic xx.\n",
+    "       01  ws-fs-status-merge                      pic xx.\n",
+    "       01  ws-fs-status-sorted                     pic xx.\n",
+    "\n",
+    "       01  ws-eof-sw                               pic x value 'N'.\n",
+    "           88  ws-eof                              value 'Y'.\n",
+    "           88  ws-not-eof                          value 'N'.\n",
+    "\n",
+    "       procedure division.\n",
+    "       main-procedure.\n",
+    "           perform create-test-data\n",
+    "\n",
+    "           perform merge-and-display-files\n",
+    "\n",
+    "           perform sort-and-display-file\n",
+    "\n",
+    "           display \"Done.\"\n",
+    "\n",
+    "           stop run.\n",
+    "\n",
+    "\n",
+    "       merge-and-display-files.\n",
+    "\n",
+    "           display \"Merging and sorting files...\"\n",
+    "\n",
+    "           merge fd-sorting-file\n",
+    "               on ascending key f-customer-id\n",
+    "               of f-customer-record-merged\n",
+    "               using fd-test-file-1 fd-test-file-2 giving fd-merged-file\n",
+    "\n",
+    "           open input fd-merged-file\n",
+    "\n",
+    "               if ws-fs-status-merge not = \"00\" then\n",
+    "                   display \"Error opening merged output file: \"\n",
+    "                       ws-fs-status-merge\n",
+    "                   end-display\n",
+    "                   stop run\n",
+    "               end-if\n",
+    "\n",
+    "               set ws-not-eof to true\n",
+    "\n",
+    "               perform until ws-eof\n",
+    "                   read fd-merged-file\n",
+    "                       at end\n",
+    "                           set ws-eof to true\n",
+    "                       not at end\n",
+    "                           display f-customer-record-merged\n",
+    "                   end-read\n",
+    "               end-perform\n",
+    "\n",
+    "           close fd-merged-file\n",
+    "\n",
+    "           exit paragraph.\n",
+    "\n",
+    "\n",
+    "\n",
+    "       sort-and-display-file.\n",
+    "\n",
+    "           display \"Sorting merged file on descending contract id....\"\n",
+    "\n",
+    "           sort fd-sorting-file\n",
+    "               on descending key f-customer-contract-id\n",
+    "               of f-customer-record-sorted-contract-id\n",
+    "               using fd-merged-file giving fd-sorted-contract-id\n",
+    "\n",
+    "           open input fd-sorted-contract-id\n",
+    "\n",
+    "               if ws-fs-status-sorted not = \"00\" then\n",
+    "                   display \"Error opening sorted output file: \"\n",
+    "                       ws-fs-status-sorted\n",
+    "                   end-display\n",
+    "                   stop run\n",
+    "               end-if\n",
+    "\n",
+    "               set ws-not-eof to true\n",
+    "\n",
+    "               perform until ws-eof\n",
+    "                   read fd-sorted-contract-id\n",
+    "                       at end\n",
+    "                           set ws-eof to true\n",
+    "                       not at end\n",
+    "                           display f-customer-record-sorted-contract-id\n",
+    "                   end-read\n",
+    "               end-perform\n",
+    "\n",
+    "           close fd-sorted-contract-id\n",
+    "\n",
+    "           exit paragraph.\n",
+    "\n",
+    "\n",
+    "\n",
+    "       create-test-data.\n",
+    "\n",
+    "           display \"Creating test data files...\"\n",
+    "\n",
+    "           open output fd-test-file-1\n",
+    "               if ws-fs-status-1 not = \"00\" then\n",
+    "                   display \"Failed to open file for output: \"\n",
+    "                       ws-fs-status-1\n",
+    "                   end-display\n",
+    "                   stop run\n",
+    "               end-if\n",
+    "\n",
+    "               move 1 to f-customer-id of f-customer-record-east\n",
+    "               move \"last-1\" to f-customer-last-name\n",
+    "                   of f-customer-record-east\n",
+    "               move \"first-1\" to f-customer-first-name\n",
+    "                   of f-customer-record-east\n",
+    "               move 5423 to f-customer-contract-id\n",
+    "                   of f-customer-record-east\n",
+    "               move \"comment-1\" to f-customer-comment\n",
+    "                   of f-customer-record-east\n",
+    "\n",
+    "               write f-customer-record-east\n",
+    "\n",
+    "\n",
+    "               move 5 to f-customer-id of f-customer-record-east\n",
+    "               move \"last-5\" to f-customer-last-name\n",
+    "                   of f-customer-record-east\n",
+    "               move \"first-5\" to f-customer-first-name\n",
+    "                   of f-customer-record-east\n",
+    "               move 12323 to f-customer-contract-id\n",
+    "                   of f-customer-record-east\n",
+    "               move \"comment-5\" to f-customer-comment\n",
+    "                   of f-customer-record-east\n",
+    "\n",
+    "               write f-customer-record-east\n",
+    "\n",
+    "\n",
+    "               move 10 to f-customer-id of f-customer-record-east\n",
+    "               move \"last-10\" to f-customer-last-name\n",
+    "                   of f-customer-record-east\n",
+    "               move \"first-10\" to f-customer-first-name\n",
+    "                   of f-customer-record-east\n",
+    "               move 653 to f-customer-contract-id\n",
+    "                   of f-customer-record-east\n",
+    "               move \"comment-10\" to f-customer-comment\n",
+    "                   of f-customer-record-east\n",
+    "\n",
+    "               write f-customer-record-east\n",
+    "\n",
+    "\n",
+    "               move 50 to f-customer-id of f-customer-record-east\n",
+    "               move \"last-50\" to f-customer-last-name\n",
+    "                   of f-customer-record-east\n",
+    "               move \"first-50\" to f-customer-first-name\n",
+    "                   of f-customer-record-east\n",
+    "               move 5050 to f-customer-contract-id\n",
+    "                   of f-customer-record-east\n",
+    "               move \"comment-50\" to f-customer-comment\n",
+    "                   of f-customer-record-east\n",
+    "\n",
+    "               write f-customer-record-east\n",
+    "\n",
+    "               move 25 to f-customer-id of f-customer-record-east\n",
+    "               move \"last-25\" to f-customer-last-name\n",
+    "                   of f-customer-record-east\n",
+    "               move \"first-25\" to f-customer-first-name\n",
+    "                   of f-customer-record-east\n",
+    "               move 7725 to f-customer-contract-id\n",
+    "                   of f-customer-record-east\n",
+    "               move \"comment-25\" to f-customer-comment\n",
+    "                   of f-customer-record-east\n",
+    "\n",
+    "               write f-customer-record-east\n",
+    "\n",
+    "\n",
+    "               move 75 to f-customer-id of f-customer-record-east\n",
+    "               move \"last-75\" to f-customer-last-name\n",
+    "                   of f-customer-record-east\n",
+    "               move \"first-75\" to f-customer-first-name\n",
+    "                   of f-customer-record-east\n",
+    "               move 1175 to f-customer-contract-id\n",
+    "                   of f-customer-record-east\n",
+    "               move \"comment-75\" to f-customer-comment\n",
+    "                   of f-customer-record-east\n",
+    "\n",
+    "               write f-customer-record-east\n",
+    "           close fd-test-file-1\n",
+    "\n",
+    "\n",
+    "\n",
+    "           open output fd-test-file-2\n",
+    "               if ws-fs-status-2 not = \"00\" then\n",
+    "                   display \"Failed to open file for output: \"\n",
+    "                       ws-fs-status-2\n",
+    "                   end-display\n",
+    "                   stop run\n",
+    "               end-if\n",
+    "\n",
+    "               move 999 to f-customer-id of f-customer-record-west\n",
+    "               move \"last-999\" to f-customer-last-name\n",
+    "                   of f-customer-record-west\n",
+    "               move \"first-999\" to f-customer-first-name\n",
+    "                   of f-customer-record-west\n",
+    "               move 1610 to f-customer-contract-id\n",
+    "                   of f-customer-record-west\n",
+    "               move \"comment-99\" to f-customer-comment\n",
+    "                   of f-customer-record-west\n",
+    "\n",
+    "               write f-customer-record-west\n",
+    "\n",
+    "\n",
+    "               move 3 to f-customer-id of f-customer-record-west\n",
+    "               move \"last-03\" to f-customer-last-name\n",
+    "                   of f-customer-record-west\n",
+    "               move \"first-03\" to f-customer-first-name\n",
+    "                   of f-customer-record-west\n",
+    "               move 3331 to f-customer-contract-id\n",
+    "                   of f-customer-record-west\n",
+    "               move \"comment-03\" to f-customer-comment\n",
+    "                   of f-customer-record-west\n",
+    "\n",
+    "               write f-customer-record-west\n",
+    "\n",
+    "               move 30 to f-customer-id of f-customer-record-west\n",
+    "               move \"last-30\" to f-customer-last-name\n",
+    "                   of f-customer-record-west\n",
+    "               move \"first-30\" to f-customer-first-name\n",
+    "                   of f-customer-record-west\n",
+    "               move 8765 to f-customer-contract-id\n",
+    "                   of f-customer-record-west\n",
+    "               move \"comment-30\" to f-customer-comment\n",
+    "                   of f-customer-record-west\n",
+    "\n",
+    "               write f-customer-record-west\n",
+    "\n",
+    "\n",
+    "               move 85 to f-customer-id of f-customer-record-west\n",
+    "               move \"last-85\" to f-customer-last-name\n",
+    "                   of f-customer-record-west\n",
+    "               move \"first-85\" to f-customer-first-name\n",
+    "                   of f-customer-record-west\n",
+    "               move 4567 to f-customer-contract-id\n",
+    "                   of f-customer-record-west\n",
+    "               move \"comment-85\" to f-customer-comment\n",
+    "                   of f-customer-record-west\n",
+    "\n",
+    "               write f-customer-record-west\n",
+    "\n",
+    "\n",
+    "               move 24 to f-customer-id of f-customer-record-west\n",
+    "               move \"last-24\" to f-customer-last-name\n",
+    "                   of f-customer-record-west\n",
+    "               move \"first-24\" to f-customer-first-name\n",
+    "                   of f-customer-record-west\n",
+    "               move 247 to f-customer-contract-id\n",
+    "                   of f-customer-record-west\n",
+    "               move \"comment-24\" to f-customer-comment\n",
+    "                   of f-customer-record-west\n",
+    "\n",
+    "               write f-customer-record-west\n",
+    "\n",
+    "           close fd-test-file-2\n",
+    "\n",
+    "\n",
+    "           exit paragraph.\n",
+    "\n",
+    "       end program merge-sort-example.\n",
+    "       \"\"\"\n",
+    "\n",
+    "PYTHON_FILE = \"\"\"from __future__ import annotations\n",
+    "\n",
+    "from decimal import Decimal\n",
+    "\n",
+    "from numpy import array\n",
+    "\n",
+    "\n",
+    "def inverse_of_matrix(matrix: list[list[float]]) -> list[list[float]]:\n",
+    "\n",
+    "    d = Decimal\n",
+    "\n",
+    "    # Check if the provided matrix has 2 rows and 2 columns\n",
+    "    # since this implementation only works for 2x2 matrices\n",
+    "    if len(matrix) == 2 and len(matrix[0]) == 2 and len(matrix[1]) == 2:\n",
+    "        # Calculate the determinant of the matrix\n",
+    "        determinant = float(\n",
+    "            d(matrix[0][0]) * d(matrix[1][1]) - d(matrix[1][0]) * d(matrix[0][1])\n",
+    "        )\n",
+    "        if determinant == 0:\n",
+    "            raise ValueError(\"This matrix has no inverse.\")\n",
+    "\n",
+    "        # Creates a copy of the matrix with swapped positions of the elements\n",
+    "        swapped_matrix = [[0.0, 0.0], [0.0, 0.0]]\n",
+    "        swapped_matrix[0][0], swapped_matrix[1][1] = matrix[1][1], matrix[0][0]\n",
+    "        swapped_matrix[1][0], swapped_matrix[0][1] = -matrix[1][0], -matrix[0][1]\n",
+    "\n",
+    "        # Calculate the inverse of the matrix\n",
+    "        return [\n",
+    "            [(float(d(n)) / determinant) or 0.0 for n in row] for row in swapped_matrix\n",
+    "        ]\n",
+    "    elif (\n",
+    "        len(matrix) == 3\n",
+    "        and len(matrix[0]) == 3\n",
+    "        and len(matrix[1]) == 3\n",
+    "        and len(matrix[2]) == 3\n",
+    "    ):\n",
+    "        # Calculate the determinant of the matrix using Sarrus rule\n",
+    "        determinant = float(\n",
+    "            (\n",
+    "                (d(matrix[0][0]) * d(matrix[1][1]) * d(matrix[2][2]))\n",
+    "                + (d(matrix[0][1]) * d(matrix[1][2]) * d(matrix[2][0]))\n",
+    "                + (d(matrix[0][2]) * d(matrix[1][0]) * d(matrix[2][1]))\n",
+    "            )\n",
+    "            - (\n",
+    "                (d(matrix[0][2]) * d(matrix[1][1]) * d(matrix[2][0]))\n",
+    "                + (d(matrix[0][1]) * d(matrix[1][0]) * d(matrix[2][2]))\n",
+    "                + (d(matrix[0][0]) * d(matrix[1][2]) * d(matrix[2][1]))\n",
+    "            )\n",
+    "        )\n",
+    "        if determinant == 0:\n",
+    "            raise ValueError(\"This matrix has no inverse.\")\n",
+    "\n",
+    "        # Creating cofactor matrix\n",
+    "        cofactor_matrix = [\n",
+    "            [d(0.0), d(0.0), d(0.0)],\n",
+    "            [d(0.0), d(0.0), d(0.0)],\n",
+    "            [d(0.0), d(0.0), d(0.0)],\n",
+    "        ]\n",
+    "        cofactor_matrix[0][0] = (d(matrix[1][1]) * d(matrix[2][2])) - (\n",
+    "            d(matrix[1][2]) * d(matrix[2][1])\n",
+    "        )\n",
+    "        cofactor_matrix[0][1] = -(\n",
+    "            (d(matrix[1][0]) * d(matrix[2][2])) - (d(matrix[1][2]) * d(matrix[2][0]))\n",
+    "        )\n",
+    "        cofactor_matrix[0][2] = (d(matrix[1][0]) * d(matrix[2][1])) - (\n",
+    "            d(matrix[1][1]) * d(matrix[2][0])\n",
+    "        )\n",
+    "        cofactor_matrix[1][0] = -(\n",
+    "            (d(matrix[0][1]) * d(matrix[2][2])) - (d(matrix[0][2]) * d(matrix[2][1]))\n",
+    "        )\n",
+    "        cofactor_matrix[1][1] = (d(matrix[0][0]) * d(matrix[2][2])) - (\n",
+    "            d(matrix[0][2]) * d(matrix[2][0])\n",
+    "        )\n",
+    "        cofactor_matrix[1][2] = -(\n",
+    "            (d(matrix[0][0]) * d(matrix[2][1])) - (d(matrix[0][1]) * d(matrix[2][0]))\n",
+    "        )\n",
+    "        cofactor_matrix[2][0] = (d(matrix[0][1]) * d(matrix[1][2])) - (\n",
+    "            d(matrix[0][2]) * d(matrix[1][1])\n",
+    "        )\n",
+    "        cofactor_matrix[2][1] = -(\n",
+    "            (d(matrix[0][0]) * d(matrix[1][2])) - (d(matrix[0][2]) * d(matrix[1][0]))\n",
+    "        )\n",
+    "        cofactor_matrix[2][2] = (d(matrix[0][0]) * d(matrix[1][1])) - (\n",
+    "            d(matrix[0][1]) * d(matrix[1][0])\n",
+    "        )\n",
+    "\n",
+    "        # Transpose the cofactor matrix (Adjoint matrix)\n",
+    "        adjoint_matrix = array(cofactor_matrix)\n",
+    "        for i in range(3):\n",
+    "            for j in range(3):\n",
+    "                adjoint_matrix[i][j] = cofactor_matrix[j][i]\n",
+    "\n",
+    "        # Inverse of the matrix using the formula (1/determinant) * adjoint matrix\n",
+    "        inverse_matrix = array(cofactor_matrix)\n",
+    "        for i in range(3):\n",
+    "            for j in range(3):\n",
+    "                inverse_matrix[i][j] /= d(determinant)\n",
+    "\n",
+    "        # Calculate the inverse of the matrix\n",
+    "        return [[float(d(n)) or 0.0 for n in row] for row in inverse_matrix]\n",
+    "    raise ValueError(\"Please provide a matrix of size 2x2 or 3x3.\")\n",
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "722c7818-f8e5-4b9f-a18d-b2bad6232c01",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "num_examples = 100\n",
+    "known_cobol__examples = generate_fim_examples(KNOWN_COBOL_FILE,num_examples,np.random.default_rng(1))\n",
+    "unknown_cobol_examples = generate_fim_examples(NEW_COBOL_FILE,num_examples,np.random.default_rng(1))\n",
+    "python_code_base_examples = generate_fim_examples(PYTHON_FILE,num_examples,np.random.default_rng(1))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d413db76-af2f-46da-818c-b694a6747c42",
+   "metadata": {},
+   "source": [
+    "## Step 3.2 Run and implement evaluation "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "12acc436-b43e-4196-aaf7-9d7c92b87d24",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "codestral_finetuned = retrieved_job.fine_tuned_model\n",
+    "codestral = \"codestral-latest\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "6f676701-ad20-4e98-9309-256dec55dad6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def answer_example(model, example):\n",
+    "    \"\"\"\n",
+    "    Generate a response for a given example using the specified model and update the example with the suggestion.\n",
+    "\n",
+    "    Args:\n",
+    "    model (str): The model to use for generating the response.\n",
+    "    example (dict): The example containing 'prefix' and 'suffix'.\n",
+    "\n",
+    "    Returns:\n",
+    "    dict: The updated example with the 'suggestion' added.\n",
+    "    \"\"\"\n",
+    "\n",
+    "    # Wait for 1 second (if you are using a free tier with specific rate limit)\n",
+    "    time.sleep(1)\n",
+    "\n",
+    "    # Generate a response using the model\n",
+    "    response = client.fim.complete(\n",
+    "        model=model,\n",
+    "        prompt=example['prefix'],\n",
+    "        suffix=example['suffix'],\n",
+    "        temperature=0,\n",
+    "        top_p=1,\n",
+    "        max_tokens=1000,\n",
+    "        stop=[\"\\n\"]\n",
+    "    )\n",
+    "\n",
+    "    # Extract the suggestion from the response\n",
+    "    suggestion = response.choices[0].message.content\n",
+    "\n",
+    "    # Update the example with the suggestion\n",
+    "    example['suggestion'] = suggestion\n",
+    "\n",
+    "    return example\n",
+    "\n",
+    "def evaluate_model(model, examples):\n",
+    "    \"\"\"\n",
+    "    Evaluate the model's performance on a list of examples.\n",
+    "\n",
+    "    Args:\n",
+    "    model (str): The model to evaluate.\n",
+    "    examples (list): A list of examples to evaluate the model on.\n",
+    "\n",
+    "    Returns:\n",
+    "    float: The average accuracy of the model across all examples.\n",
+    "    \"\"\"\n",
+    "    # Generate answers for all examples\n",
+    "    examples_with_answer = [answer_example(model, example) for example in examples]\n",
+    "\n",
+    "    # Evaluate the accuracy of each example\n",
+    "    matches = [example['answer'].replace('\\n', '')==example['suggestion'].replace('\\n', '') for example in examples_with_answer]\n",
+    "\n",
+    "    # Return the average accuracy\n",
+    "    return np.mean(matches)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "14db9b09-8386-499d-b808-0a3207fc6217",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'codestral': {'cobol_file_from_repo': 0.5324675324675324,\n",
+       "  'cobol_file_new': 0.8372093023255814,\n",
+       "  'python_file_new': 0.7384615384615385},\n",
+       " 'codestral_finetuned': {'cobol_file_from_repo': 0.8701298701298701,\n",
+       "  'cobol_file_new': 0.8488372093023255,\n",
+       "  'python_file_new': 0.7384615384615385}}"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "accuracies = {\n",
+    "    'codestral': {\n",
+    "        'cobol_file_from_repo': evaluate_model(codestral,known_cobol__examples),\n",
+    "        'cobol_file_new': evaluate_model(codestral,unknown_cobol_examples),\n",
+    "        'python_file_new': evaluate_model(codestral,python_code_base_examples)\n",
+    "    },\n",
+    "    'codestral_finetuned': {\n",
+    "        'cobol_file_from_repo': evaluate_model(codestral_finetuned,known_cobol__examples),\n",
+    "        'cobol_file_new': evaluate_model(codestral_finetuned,unknown_cobol_examples),\n",
+    "        'python_file_new': evaluate_model(codestral_finetuned,python_code_base_examples)\n",
+    "    }\n",
+    "}\n",
+    "\n",
+    "accuracies"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "acbb5f1f-cbb1-49b4-8410-72326d00a632",
+   "metadata": {},
+   "source": [
+    "## Step 3.3 Display results "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "d2e9a38b-5c9c-45d2-a826-1efa8b5f50fd",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "models = list(accuracies.keys())\n",
+    "files = list(accuracies['codestral'].keys())\n",
+    "\n",
+    "# Prepare data for plotting\n",
+    "performance = {model: [accuracies[model][file] for file in files] for model in models}\n",
+    "\n",
+    "# Bar width\n",
+    "bar_width = 0.35\n",
+    "\n",
+    "# Positions for the bars\n",
+    "r = np.arange(len(files))\n",
+    "\n",
+    "# Create the plot\n",
+    "plt.figure(figsize=(12, 8))  # Adjust the figure size here\n",
+    "\n",
+    "colors = ['orange', 'darkorange']  # Colors for each model\n",
+    "\n",
+    "for i, model in enumerate(models):\n",
+    "    plt.bar(r + i * bar_width, performance[model], width=bar_width, color=colors[i], label=model, edgecolor='black', linewidth=1.2)\n",
+    "\n",
+    "# Add labels and title\n",
+    "plt.xlabel('Files', fontweight='bold', fontsize=14)\n",
+    "plt.ylabel(f'Next line accuracy on {num_examples} examples', fontweight='bold', fontsize=14)\n",
+    "plt.title('Finetune Codestral on Cobol repo', fontweight='bold', fontsize=16)\n",
+    "plt.xticks(r + bar_width / 2, files, fontsize=12, rotation=15)\n",
+    "plt.yticks(np.arange(0, 1.1, 0.1))  # Add more ticks on the y-axis\n",
+    "\n",
+    "# Add a legend\n",
+    "plt.legend(title='Models', fontsize=12, title_fontsize=13)\n",
+    "\n",
+    "# Add grid for better readability\n",
+    "plt.grid(axis='y', linestyle='--', alpha=0.7)\n",
+    "\n",
+    "# Add a background color\n",
+    "plt.gca().set_facecolor('#f0f0f0')\n",
+    "\n",
+    "# Show the plot\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "mistral_3",
+   "language": "python",
+   "name": "mistral_3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}