dodanie plikóœ certyfikatóœ

Dodanie certyfikatu PDF
commit - koniec treningu
2026-09-07 10:29:26 +02:00 · 2025-05-26 10:55:01 +02:00 · 2025-05-21 15:27:00 +02:00 · 2025-05-21 10:35:44 +02:00 · 2025-05-20 15:37:05 +02:00 · 2025-05-20 14:33:46 +02:00
13 changed files with 59423 additions and 262 deletions
--- a/Certyfikaty/Adv_ML_Stanczew.pdf
+++ b/Certyfikaty/Adv_ML_Stanczew.pdf
--- a/Certyfikaty/Altkom_AdvC++.pdf
+++ b/Certyfikaty/Altkom_AdvC++.pdf
--- a/Certyfikaty/NobleProg
+++ b/Certyfikaty/NobleProg
--- a/PythonAI/JupyterLab/.gitignore
+++ b/PythonAI/JupyterLab/.gitignore
@ -0,0 +1,3 @@
+data
+model_checkpoints
+logs
--- a/PythonAI/JupyterLab/Cwiczenie1.ipynb
+++ b/PythonAI/JupyterLab/Cwiczenie1.ipynb
@ -18,7 +18,7 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": 1,
   "id": "178ae645-cad9-491c-9a26-c173eda34a00",
   "metadata": {},
   "outputs": [],
@ -29,7 +29,7 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 2,
   "id": "540f9f69-d932-4b5a-8d70-e18a08bdcf46",
   "metadata": {},
   "outputs": [
@ -245,7 +245,7 @@
       "[481 rows x 10 columns]"
      ]
     },
-     "execution_count": 47,
+     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
@ -268,7 +268,7 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 48,
+   "execution_count": 3,
   "id": "62e61e9e-f06e-4124-9a89-1979dc071c47",
   "metadata": {},
   "outputs": [
@ -496,7 +496,7 @@
       "[481 rows x 11 columns]"
      ]
     },
-     "execution_count": 48,
+     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
@ -521,7 +521,7 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 4,
   "id": "e06e7a55-1837-456b-97ef-4c58276bd7b6",
   "metadata": {},
   "outputs": [
@ -749,7 +749,7 @@
       "[481 rows x 11 columns]"
      ]
     },
-     "execution_count": 49,
+     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
@ -773,7 +773,7 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 50,
+   "execution_count": 5,
   "id": "389f0c22-b210-45f3-9627-02c06d255a69",
   "metadata": {},
   "outputs": [],
@ -793,7 +793,7 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 51,
+   "execution_count": 6,
   "id": "60362a3d-91ab-4666-bf26-afdeb3cd5c9c",
   "metadata": {},
   "outputs": [],
@ -805,7 +805,7 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 52,
+   "execution_count": 7,
   "id": "a68dd0eb-6085-483b-99f3-a540a35515c2",
   "metadata": {},
   "outputs": [],
@ -821,7 +821,7 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 53,
+   "execution_count": 8,
   "id": "bb4ecdab-2136-4970-a38d-6eaec8ec92ae",
   "metadata": {},
   "outputs": [
@ -1049,7 +1049,7 @@
       "[481 rows x 11 columns]"
      ]
     },
-     "execution_count": 53,
+     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
@ -1060,7 +1060,7 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 54,
+   "execution_count": 9,
   "id": "7c8199c4-9d1b-405a-9cda-b2aef1616999",
   "metadata": {},
   "outputs": [
@ -1201,7 +1201,7 @@
       "std             0.159067                 0.0    0.159067  "
      ]
     },
-     "execution_count": 54,
+     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
@ -1212,7 +1212,7 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 55,
+   "execution_count": 10,
   "id": "7468e63c-c72b-4150-bd40-6f6e61f17af8",
   "metadata": {},
   "outputs": [
@ -1381,7 +1381,7 @@
       "std      0.176697  "
      ]
     },
-     "execution_count": 55,
+     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
@ -1400,7 +1400,7 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": 12,
   "id": "efa6a165-9988-420f-a2f0-10cbbcd5dc39",
   "metadata": {},
   "outputs": [
@ -1442,7 +1442,7 @@
       "      <td>249.000000</td>\n",
       "      <td>249.000000</td>\n",
       "      <td>249.000000</td>\n",
-       "      <td>157.000000</td>\n",
+       "      <td>249.000000</td>\n",
       "      <td>249.000000</td>\n",
       "      <td>249.000000</td>\n",
       "      <td>249.000000</td>\n",
@ -1454,7 +1454,7 @@
       "      <td>16.004819</td>\n",
       "      <td>6.371486</td>\n",
       "      <td>8.712048</td>\n",
-       "      <td>0.364968</td>\n",
+       "      <td>0.230120</td>\n",
       "      <td>4.080321</td>\n",
       "      <td>8.360241</td>\n",
       "      <td>0.048193</td>\n",
@ -1466,7 +1466,7 @@
       "      <td>11.000615</td>\n",
       "      <td>10.157809</td>\n",
       "      <td>9.936468</td>\n",
-       "      <td>2.679477</td>\n",
+       "      <td>2.132453</td>\n",
       "      <td>26.325536</td>\n",
       "      <td>15.718945</td>\n",
       "      <td>0.249368</td>\n",
@ -1539,9 +1539,9 @@
      ],
      "text/plain": [
       "             TMAX        TMIN        TOBS        WESF        SNOW        PRCP  \\\n",
-       "count  249.000000  249.000000  249.000000  157.000000  249.000000  249.000000   \n",
-       "mean    16.004819    6.371486    8.712048    0.364968    4.080321    8.360241   \n",
-       "std     11.000615   10.157809    9.936468    2.679477   26.325536   15.718945   \n",
+       "count  249.000000  249.000000  249.000000  249.000000  249.000000  249.000000   \n",
+       "mean    16.004819    6.371486    8.712048    0.230120    4.080321    8.360241   \n",
+       "std     11.000615   10.157809    9.936468    2.132453   26.325536   15.718945   \n",
       "min    -11.700000  -17.200000  -16.100000    0.000000    0.000000    0.000000   \n",
       "25%      6.700000   -1.700000    0.000000    0.000000    0.000000    0.000000   \n",
       "50%     14.400000    5.600000    8.300000    0.000000    0.000000    0.300000   \n",
@ -1559,7 +1559,7 @@
       "max             2.000000            1.000000    2.000000  "
      ]
     },
-     "execution_count": 45,
+     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
@ -1571,6 +1571,7 @@
    "df_merged[\"incl_weather_true\"] = df_merged.incl_weather_true_temp.fillna(0) + df_merged.incl_weather_true_snow.fillna(0)\n",
    "df_merged[\"incl_weather_false\"] = df_merged.incl_weather_false_temp.fillna(0) + df_merged.incl_weather_false_snow.fillna(0)\n",
    "df_merged[\"snow\"] = df_merged.snow_temp.fillna(0) + df_merged.snow_snow.fillna(0)\n",
+    "df_merged['WESF'] = df_merged['WESF'].fillna(0)\n",
    "\n",
    "del df_merged[\"PRCP_temp\"]\n",
    "del df_merged[\"PRCP_snow\"]\n",
@ -1612,7 +1613,7 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.12.2"
+   "version": "3.13.2"
  }
 },
 "nbformat": 4,
--- a/PythonAI/JupyterLab/DQNCartPole.ipynb
+++ b/PythonAI/JupyterLab/DQNCartPole.ipynb
--- a/PythonAI/JupyterLab/Pipfile
+++ b/PythonAI/JupyterLab/Pipfile
@ -5,13 +5,24 @@ name = "pypi"

 [packages]
 jupyterlab = "*"
+jupyterlab-vim = "*"
+notebook-intelligence = "*"
 pandas = "*"
 numpy = "*"
 scikit-learn = "*"
 sklearn-pandas = "*"
 matplotlib = "*"
+tensorflow = "*"
+torch = "*"
+torchvision = "*"
+ultralytics = "*"
+statsmodels = "*"
+accelerate = "*"
+datasets = "*"
+h2o = "*"

 [dev-packages]

 [requires]
-python_version = "3.13"
+python_version = "3.12"
+# python_version = "3.13"
--- a/PythonAI/JupyterLab/PythonAI_4.ipynb
+++ b/PythonAI/JupyterLab/PythonAI_4.ipynb
--- a/PythonAI/JupyterLab/PythonAI_5.ipynb
+++ b/PythonAI/JupyterLab/PythonAI_5.ipynb
--- a/PythonAI/JupyterLab/PythonAI_7.ipynb
+++ b/PythonAI/JupyterLab/PythonAI_7.ipynb
--- a/PythonAI/JupyterLab/llm_test.ipynb
+++ b/PythonAI/JupyterLab/llm_test.ipynb
@ -0,0 +1,413 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "7018890b-b220-48a3-a1b8-d8f6c5483f6c",
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...\n",
+      "To disable this warning, you can either:\n",
+      "\t- Avoid using `tokenizers` before the fork if possible\n",
+      "\t- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Cloning into 'gpt-neo-125M'...\n",
+      "remote: Enumerating objects: 65, done.\u001b[K\n",
+      "remote: Counting objects: 100% (5/5), done.\u001b[K\n",
+      "remote: Compressing objects: 100% (5/5), done.\u001b[K\n",
+      "remote: Total 65 (delta 1), reused 0 (delta 0), pack-reused 60 (from 1)\u001b[K\n",
+      "Unpacking objects: 100% (65/65), 1.11 MiB | 9.13 MiB/s, done.\n",
+      "Filtering content: 100% (4/4), 1.93 GiB | 54.88 MiB/s, done.\n"
+     ]
+    }
+   ],
+   "source": [
+    "!git clone https://huggingface.co/EleutherAI/gpt-neo-125M"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "36078c20-4185-4f45-84f2-d3e95e1dcac9",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[33mDEPRECATION: Loading egg at /usr/local/lib/python3.12/dist-packages/nvfuser-0.2.13a0+0d33366-py3.12-linux-x86_64.egg is deprecated. pip 25.1 will enforce this behaviour change. A possible replacement is to use pip for package installation. Discussion can be found at https://github.com/pypa/pip/issues/12330\u001b[0m\u001b[33m\n",
+      "\u001b[0m\u001b[33mDEPRECATION: Loading egg at /usr/local/lib/python3.12/dist-packages/dill-0.3.9-py3.12.egg is deprecated. pip 25.1 will enforce this behaviour change. A possible replacement is to use pip for package installation. Discussion can be found at https://github.com/pypa/pip/issues/12330\u001b[0m\u001b[33m\n",
+      "\u001b[0m\u001b[33mDEPRECATION: Loading egg at /usr/local/lib/python3.12/dist-packages/lightning_utilities-0.11.8-py3.12.egg is deprecated. pip 25.1 will enforce this behaviour change. A possible replacement is to use pip for package installation. Discussion can be found at https://github.com/pypa/pip/issues/12330\u001b[0m\u001b[33m\n",
+      "\u001b[0m\u001b[33mDEPRECATION: Loading egg at /usr/local/lib/python3.12/dist-packages/opt_einsum-3.4.0-py3.12.egg is deprecated. pip 25.1 will enforce this behaviour change. A possible replacement is to use pip for package installation. Discussion can be found at https://github.com/pypa/pip/issues/12330\u001b[0m\u001b[33m\n",
+      "\u001b[0m\u001b[33mDEPRECATION: Loading egg at /usr/local/lib/python3.12/dist-packages/igraph-0.11.8-py3.12-linux-x86_64.egg is deprecated. pip 25.1 will enforce this behaviour change. A possible replacement is to use pip for package installation. Discussion can be found at https://github.com/pypa/pip/issues/12330\u001b[0m\u001b[33m\n",
+      "\u001b[0m\u001b[33mDEPRECATION: Loading egg at /usr/local/lib/python3.12/dist-packages/lightning_thunder-0.2.0.dev0-py3.12.egg is deprecated. pip 25.1 will enforce this behaviour change. A possible replacement is to use pip for package installation. Discussion can be found at https://github.com/pypa/pip/issues/12330\u001b[0m\u001b[33m\n",
+      "\u001b[0m\u001b[33mDEPRECATION: Loading egg at /usr/local/lib/python3.12/dist-packages/texttable-1.7.0-py3.12.egg is deprecated. pip 25.1 will enforce this behaviour change. A possible replacement is to use pip for package installation. Discussion can be found at https://github.com/pypa/pip/issues/12330\u001b[0m\u001b[33m\n",
+      "\u001b[0m\u001b[33mDEPRECATION: Loading egg at /usr/local/lib/python3.12/dist-packages/looseversion-1.3.0-py3.12.egg is deprecated. pip 25.1 will enforce this behaviour change. A possible replacement is to use pip for package installation. Discussion can be found at https://github.com/pypa/pip/issues/12330\u001b[0m\u001b[33m\n",
+      "\u001b[0m\n",
+      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m24.3.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m25.1.1\u001b[0m\n",
+      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpython -m pip install --upgrade pip\u001b[0m\n"
+     ]
+    }
+   ],
+   "source": [
+    "!pip install accelerate>=0.26.0"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "11d0a83e-391e-4590-9db6-6a2a3c140ae2",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...\n",
+      "To disable this warning, you can either:\n",
+      "\t- Avoid using `tokenizers` before the fork if possible\n",
+      "\t- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[33mDEPRECATION: Loading egg at /usr/local/lib/python3.12/dist-packages/nvfuser-0.2.13a0+0d33366-py3.12-linux-x86_64.egg is deprecated. pip 25.1 will enforce this behaviour change. A possible replacement is to use pip for package installation. Discussion can be found at https://github.com/pypa/pip/issues/12330\u001b[0m\u001b[33m\n",
+      "\u001b[0m\u001b[33mDEPRECATION: Loading egg at /usr/local/lib/python3.12/dist-packages/dill-0.3.9-py3.12.egg is deprecated. pip 25.1 will enforce this behaviour change. A possible replacement is to use pip for package installation. Discussion can be found at https://github.com/pypa/pip/issues/12330\u001b[0m\u001b[33m\n",
+      "\u001b[0m\u001b[33mDEPRECATION: Loading egg at /usr/local/lib/python3.12/dist-packages/lightning_utilities-0.11.8-py3.12.egg is deprecated. pip 25.1 will enforce this behaviour change. A possible replacement is to use pip for package installation. Discussion can be found at https://github.com/pypa/pip/issues/12330\u001b[0m\u001b[33m\n",
+      "\u001b[0m\u001b[33mDEPRECATION: Loading egg at /usr/local/lib/python3.12/dist-packages/opt_einsum-3.4.0-py3.12.egg is deprecated. pip 25.1 will enforce this behaviour change. A possible replacement is to use pip for package installation. Discussion can be found at https://github.com/pypa/pip/issues/12330\u001b[0m\u001b[33m\n",
+      "\u001b[0m\u001b[33mDEPRECATION: Loading egg at /usr/local/lib/python3.12/dist-packages/igraph-0.11.8-py3.12-linux-x86_64.egg is deprecated. pip 25.1 will enforce this behaviour change. A possible replacement is to use pip for package installation. Discussion can be found at https://github.com/pypa/pip/issues/12330\u001b[0m\u001b[33m\n",
+      "\u001b[0m\u001b[33mDEPRECATION: Loading egg at /usr/local/lib/python3.12/dist-packages/lightning_thunder-0.2.0.dev0-py3.12.egg is deprecated. pip 25.1 will enforce this behaviour change. A possible replacement is to use pip for package installation. Discussion can be found at https://github.com/pypa/pip/issues/12330\u001b[0m\u001b[33m\n",
+      "\u001b[0m\u001b[33mDEPRECATION: Loading egg at /usr/local/lib/python3.12/dist-packages/texttable-1.7.0-py3.12.egg is deprecated. pip 25.1 will enforce this behaviour change. A possible replacement is to use pip for package installation. Discussion can be found at https://github.com/pypa/pip/issues/12330\u001b[0m\u001b[33m\n",
+      "\u001b[0m\u001b[33mDEPRECATION: Loading egg at /usr/local/lib/python3.12/dist-packages/looseversion-1.3.0-py3.12.egg is deprecated. pip 25.1 will enforce this behaviour change. A possible replacement is to use pip for package installation. Discussion can be found at https://github.com/pypa/pip/issues/12330\u001b[0m\u001b[33m\n",
+      "\u001b[0m\n",
+      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m24.3.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m25.1.1\u001b[0m\n",
+      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpython -m pip install --upgrade pip\u001b[0m\n"
+     ]
+    }
+   ],
+   "source": [
+    "!pip install datasets transformers torch gradio --quiet"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "7057ed8b-c98c-446e-b40b-2de8a800cb7c",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/usr/local/lib/python3.12/dist-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
+      "  from .autonotebook import tqdm as notebook_tqdm\n"
+     ]
+    }
+   ],
+   "source": [
+    "from transformers import AutoTokenizer, AutoModelForCausalLM\n",
+    "import torch\n",
+    "\n",
+    "# Ścieżka do lokalnego modelu\n",
+    "local_model_path = \"./gpt-neo-125M\"\n",
+    "\n",
+    "# Załaduj tokenizer i model w trybie offline\n",
+    "tokenizer = AutoTokenizer.from_pretrained(local_model_path, local_files_only=True)\n",
+    "tokenizer.pad_token = tokenizer.eos_token\n",
+    "model = AutoModelForCausalLM.from_pretrained(local_model_path, local_files_only=True)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "3575956e-aa32-4173-8678-9a34b838ce3c",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Map: 100%|██████████| 20/20 [00:00<00:00, 1442.80 examples/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Dataset({\n",
+      "    features: ['input_ids', 'attention_mask'],\n",
+      "    num_rows: 20\n",
+      "})\n",
+      "Liczba próbek po tokenizacji: 20\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "from datasets import Dataset\n",
+    "from transformers import AutoTokenizer, AutoModelForCausalLM, TrainingArguments, Trainer, DataCollatorForLanguageModeling\n",
+    "\n",
+    "# Ścieżka do lokalnego modelu\n",
+    "local_model_path = \"./gpt-neo-125M\"\n",
+    "\n",
+    "# Tokenizer\n",
+    "tokenizer = AutoTokenizer.from_pretrained(local_model_path, local_files_only=True)\n",
+    "tokenizer.pad_token = tokenizer.eos_token  # <-- wymagane do paddingu\n",
+    "\n",
+    "# Wczytanie danych z pliku\n",
+    "with open(\"data.txt\", encoding=\"utf-8\") as f:\n",
+    "    lines = [line.strip() for line in f if line.strip()]  # Usuwamy puste linie\n",
+    "\n",
+    "# Budujemy Dataset z listy słowników\n",
+    "data = [{\"text\": line} for line in lines]\n",
+    "raw_dataset = Dataset.from_list(data)\n",
+    "\n",
+    "# Funkcja tokenizująca\n",
+    "def tokenize_function(example):\n",
+    "    return tokenizer(\n",
+    "        example[\"text\"],\n",
+    "        truncation=True,\n",
+    "        max_length=128,\n",
+    "        padding=\"max_length\"\n",
+    "    )\n",
+    "\n",
+    "# Tokenizacja datasetu\n",
+    "tokenized_dataset = raw_dataset.map(tokenize_function, batched=True, remove_columns=[\"text\"])\n",
+    "\n",
+    "# Sprawdź czy dane są OK\n",
+    "print(tokenized_dataset)\n",
+    "print(f\"Liczba próbek po tokenizacji: {len(tokenized_dataset)}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "c5eedf83-e003-434e-af7c-a57d6efdd120",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_6455/2971221750.py:23: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `Trainer.__init__`. Use `processing_class` instead.\n",
+      "  trainer = Trainer(\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "    <div>\n",
+       "      \n",
+       "      <progress value='60' max='60' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
+       "      [60/60 00:12, Epoch 3/3]\n",
+       "    </div>\n",
+       "    <table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       " <tr style=\"text-align: left;\">\n",
+       "      <th>Step</th>\n",
+       "      <th>Training Loss</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>50</td>\n",
+       "      <td>2.103000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table><p>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "('./gpt-neo-finetuned/tokenizer_config.json',\n",
+       " './gpt-neo-finetuned/special_tokens_map.json',\n",
+       " './gpt-neo-finetuned/vocab.json',\n",
+       " './gpt-neo-finetuned/merges.txt',\n",
+       " './gpt-neo-finetuned/added_tokens.json',\n",
+       " './gpt-neo-finetuned/tokenizer.json')"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Wczytanie modelu\n",
+    "model = AutoModelForCausalLM.from_pretrained(local_model_path, local_files_only=True)\n",
+    "\n",
+    "# Collator (bez maskowania)\n",
+    "data_collator = DataCollatorForLanguageModeling(\n",
+    "    tokenizer=tokenizer,\n",
+    "    mlm=False\n",
+    ")\n",
+    "\n",
+    "# Argumenty treningowe\n",
+    "training_args = TrainingArguments(\n",
+    "    output_dir=\"./gpt-neo-finetuned\",\n",
+    "    overwrite_output_dir=True,\n",
+    "    per_device_train_batch_size=1,\n",
+    "    num_train_epochs=3,\n",
+    "    save_steps=500,\n",
+    "    logging_steps=50,\n",
+    "    prediction_loss_only=True,\n",
+    "    fp16=True\n",
+    ")\n",
+    "\n",
+    "# Tworzymy Trainer\n",
+    "trainer = Trainer(\n",
+    "    model=model,\n",
+    "    args=training_args,\n",
+    "    train_dataset=tokenized_dataset,  # <-- to była literówka, nie \"train_dataset\"\n",
+    "    tokenizer=tokenizer,\n",
+    "    data_collator=data_collator\n",
+    ")\n",
+    "\n",
+    "# Start treningu\n",
+    "trainer.train()\n",
+    "\n",
+    "# Zapis modelu i tokenizer\n",
+    "trainer.save_model(\"./gpt-neo-finetuned\")\n",
+    "tokenizer.save_pretrained(\"./gpt-neo-finetuned\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "0d5c46d3-e115-4a68-9337-1f20b62a21a4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model_path = \"./gpt-neo-finetuned\"\n",
+    "\n",
+    "tokenizer = AutoTokenizer.from_pretrained(model_path)\n",
+    "model = AutoModelForCausalLM.from_pretrained(model_path)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "e656cc27-3748-4530-9ae5-05b2f8e9e105",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "* Running on local URL:  http://127.0.0.1:7863\n",
+      "* Running on public URL: https://596aa820b4401f3637.gradio.live\n",
+      "\n",
+      "This share link expires in 1 week. For free permanent hosting and GPU upgrades, run `gradio deploy` from the terminal in the working directory to deploy to Hugging Face Spaces (https://huggingface.co/spaces)\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div><iframe src=\"https://596aa820b4401f3637.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": []
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import gradio as gr\n",
+    "\n",
+    "def chat(message, chat_history):\n",
+    "    if chat_history:\n",
+    "        prompt = chat_history + f\"\\nUser: {message}\\nAI:\"\n",
+    "    else:\n",
+    "        prompt = f\"User: {message}\\nAI:\"\n",
+    "    \n",
+    "    inputs = tokenizer(prompt, return_tensors=\"pt\")\n",
+    "    outputs = model.generate(\n",
+    "        **inputs,\n",
+    "        max_length=len(inputs[\"input_ids\"][0]) + 200,\n",
+    "        temperature=0.7,\n",
+    "        pad_token_id=tokenizer.eos_token_id,\n",
+    "        do_sample=True,\n",
+    "        top_p=0.9\n",
+    "    )\n",
+    "    full_response = tokenizer.decode(outputs[0], skip_special_tokens=True)\n",
+    "    response = full_response.split(\"AI:\")[-1].strip()\n",
+    "    chat_history += f\"\\nUser: {message}\\nAI: {response}\"\n",
+    "    return chat_history, chat_history\n",
+    "\n",
+    "# Gradio UI w trybie notebookowym\n",
+    "with gr.Blocks() as demo:\n",
+    "    gr.Markdown(\"### Lokalny Czat z GPT\")\n",
+    "    chatbot_output = gr.Textbox(label=\"Historia rozmowy\", lines=20, interactive=False)\n",
+    "    user_input = gr.Textbox(label=\"Twoje pytanie\", placeholder=\"Zadaj pytanie i naciśnij Enter\")\n",
+    "    state = gr.State(\"\")\n",
+    "\n",
+    "    user_input.submit(chat, [user_input, state], [chatbot_output, state])\n",
+    "    user_input.submit(lambda: \"\", None, user_input)  # Czyści input po wysłaniu\n",
+    "\n",
+    "demo.launch(inline=True,share=True)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
--- a/PythonAI/JupyterLab/time_series_solar.csv
+++ b/PythonAI/JupyterLab/time_series_solar.csv
--- a/README.md
+++ b/README.md
@ -7,4 +7,4 @@ To jest lista traningów jakie odbyłem
 ### C/C++ Secure Coding - 18-20.03.2023
 ### Zaawansowane Tehcniki Programowania C++ - 26-26.04.2024

-### PythonAI 25-26.03.2025
+### PythonAI 25.03-21.05.2025 7 dni w 3 turach
Author	SHA1	Message	Date
Sasza Stanczew	2b2cdcacf5	dodanie plikóœ certyfikatóœ	2026-09-07 10:29:26 +02:00
sasza	ff2c034521	Dodanie certyfikatu PDF	2025-05-26 10:55:01 +02:00
Sasza Stanczew	9d960233a2	commit - koniec treningu	2025-05-21 15:27:00 +02:00
Sasza Stanczew	411baadbaa	Changes	2025-05-21 10:35:44 +02:00
Sasza Stanczew	f7c8c1badd	koniec dnia	2025-05-20 15:37:05 +02:00
Sasza Stanczew	a926d7cdd6	SimpleRNN	2025-05-20 14:33:46 +02:00
Sasza Stanczew	e3e0025eee	chang	2025-05-20 13:31:05 +02:00
Sasza Stanczew	714f2dbebf	changes	2025-05-20 12:57:26 +02:00
Sasza Stanczew	1dfffa4acf	123:x	2025-05-20 11:31:06 +02:00
sasza	92a2de0135	Dodanie notebook_intelligence itp	2025-04-10 12:04:48 +02:00