diff --git a/examples/finetune.ipynb b/examples/finetune.ipynb
index f6e4fbd1..b4ea34b2 100644
--- a/examples/finetune.ipynb
+++ b/examples/finetune.ipynb
@@ -2,18 +2,18 @@
   "cells": [
     {
       "cell_type": "code",
-      "execution_count": 1,
+      "execution_count": null,
       "metadata": {
-        "id": "Snudv-wKAR5j",
         "colab": {
           "base_uri": "https://localhost:8080/"
         },
+        "id": "Snudv-wKAR5j",
         "outputId": "bdb4b2af-872d-4ca0-f3af-ab84811c9f9c"
       },
       "outputs": [
         {
-          "output_type": "stream",
           "name": "stdout",
+          "output_type": "stream",
           "text": [
             "Collecting gliner\n",
             "  Downloading gliner-0.2.7-py3-none-any.whl (45 kB)\n",
@@ -124,28 +124,29 @@
         }
       ],
       "source": [
-        "! pip install gliner\n",
-        "! pip install accelerate -U"
+        "%%bash\n",
+        "pip uninstall gliner -y\n",
+        "rm -rf GLiNER\n",
+        "git clone https://github.com/urchade/GLiNER.git\n",
+        "cd GLiNER\n",
+        "pip install -r requirements.txt\n",
+        "pip install ."
       ]
     },
     {
       "cell_type": "code",
-      "source": [
-        "# download data\n",
-        "! wget https://huggingface.co/datasets/urchade/synthetic-pii-ner-mistral-v1/resolve/main/data.json"
-      ],
+      "execution_count": 5,
       "metadata": {
-        "id": "ETFnglCGAcSp",
         "colab": {
           "base_uri": "https://localhost:8080/"
         },
+        "id": "ETFnglCGAcSp",
         "outputId": "aea51527-910e-4c20-83d6-07df2dbbe590"
       },
-      "execution_count": 5,
       "outputs": [
         {
-          "output_type": "stream",
           "name": "stdout",
+          "output_type": "stream",
           "text": [
             "--2024-07-16 10:45:25--  https://huggingface.co/datasets/urchade/synthetic-pii-ner-mistral-v1/resolve/main/data.json\n",
             "Resolving huggingface.co (huggingface.co)... 18.164.174.118, 18.164.174.17, 18.164.174.23, ...\n",
@@ -165,6 +166,10 @@
             "\n"
           ]
         }
+      ],
+      "source": [
+        "# download data\n",
+        "! wget https://huggingface.co/datasets/urchade/synthetic-pii-ner-mistral-v1/resolve/main/data.json"
       ]
     },
     {
@@ -181,44 +186,49 @@
     },
     {
       "cell_type": "code",
-      "source": [
-        "train_path = \"data.json\"\n",
-        "\n",
-        "with open(train_path, \"r\") as f:\n",
-        "    data = json.load(f)\n",
-        "\n",
-        "print('Dataset size:', len(data))\n",
-        "\n",
-        "random.shuffle(data)\n",
-        "print('Dataset is shuffled...')\n",
-        "\n",
-        "train_dataset = data[:int(len(data)*0.9)]\n",
-        "test_dataset = data[int(len(data)*0.9):]\n",
-        "\n",
-        "print('Dataset is splitted...')"
-      ],
+      "execution_count": 7,
       "metadata": {
-        "id": "aoQdh2QAGwFf",
         "colab": {
           "base_uri": "https://localhost:8080/"
         },
+        "id": "aoQdh2QAGwFf",
         "outputId": "b9fd130b-1d4d-4f53-ce23-8feb4bffbc7d"
       },
-      "execution_count": 7,
       "outputs": [
         {
-          "output_type": "stream",
           "name": "stdout",
+          "output_type": "stream",
           "text": [
             "Dataset size: 19635\n",
             "Dataset is shuffled...\n",
             "Dataset is splitted...\n"
           ]
         }
+      ],
+      "source": [
+        "train_path = \"data.json\"\n",
+        "\n",
+        "with open(train_path, \"r\") as f:\n",
+        "    data = json.load(f)\n",
+        "\n",
+        "print('Dataset size:', len(data))\n",
+        "\n",
+        "random.shuffle(data)\n",
+        "print('Dataset is shuffled...')\n",
+        "\n",
+        "train_dataset = data[:int(len(data)*0.9)]\n",
+        "test_dataset = data[int(len(data)*0.9):]\n",
+        "\n",
+        "print('Dataset is splitted...')"
       ]
     },
     {
       "cell_type": "code",
+      "execution_count": 8,
+      "metadata": {
+        "id": "mNBNsoUjG3vH"
+      },
+      "outputs": [],
       "source": [
         "import os\n",
         "os.environ[\"TOKENIZERS_PARALLELISM\"] = \"true\"\n",
@@ -229,18 +239,12 @@
         "from gliner.data_processing.collator import DataCollatorWithPadding, DataCollator\n",
         "from gliner.utils import load_config_as_namespace\n",
         "from gliner.data_processing import WordsSplitter, GLiNERDataset"
-      ],
-      "metadata": {
-        "id": "mNBNsoUjG3vH"
-      },
-      "execution_count": 8,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
       "execution_count": 9,
       "metadata": {
-        "id": "b4X48dzJAR5m",
         "colab": {
           "base_uri": "https://localhost:8080/",
           "height": 472,
@@ -335,12 +339,13 @@
             "863316b633fd4fe88c79c7fb952b3eb7"
           ]
         },
+        "id": "b4X48dzJAR5m",
         "outputId": "f3316521-9906-4487-da0a-5b2df14e98a9"
       },
       "outputs": [
         {
-          "output_type": "stream",
           "name": "stderr",
+          "output_type": "stream",
           "text": [
             "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:89: UserWarning: \n",
             "The secret `HF_TOKEN` does not exist in your Colab secrets.\n",
@@ -351,128 +356,128 @@
           ]
         },
         {
-          "output_type": "display_data",
           "data": {
-            "text/plain": [
-              "Fetching 4 files:   0%|          | 0/4 [00:00<?, ?it/s]"
-            ],
             "application/vnd.jupyter.widget-view+json": {
+              "model_id": "a5b28bae8ed64c349c379ea088177dcd",
               "version_major": 2,
-              "version_minor": 0,
-              "model_id": "a5b28bae8ed64c349c379ea088177dcd"
-            }
+              "version_minor": 0
+            },
+            "text/plain": [
+              "Fetching 4 files:   0%|          | 0/4 [00:00<?, ?it/s]"
+            ]
           },
-          "metadata": {}
+          "metadata": {},
+          "output_type": "display_data"
         },
         {
-          "output_type": "display_data",
           "data": {
-            "text/plain": [
-              "gliner_config.json:   0%|          | 0.00/477 [00:00<?, ?B/s]"
-            ],
             "application/vnd.jupyter.widget-view+json": {
+              "model_id": "4125956c26e14685998dde6c6d323cac",
               "version_major": 2,
-              "version_minor": 0,
-              "model_id": "4125956c26e14685998dde6c6d323cac"
-            }
+              "version_minor": 0
+            },
+            "text/plain": [
+              "gliner_config.json:   0%|          | 0.00/477 [00:00<?, ?B/s]"
+            ]
           },
-          "metadata": {}
+          "metadata": {},
+          "output_type": "display_data"
         },
         {
-          "output_type": "display_data",
           "data": {
-            "text/plain": [
-              "README.md:   0%|          | 0.00/4.84k [00:00<?, ?B/s]"
-            ],
             "application/vnd.jupyter.widget-view+json": {
+              "model_id": "00c2e7114c4e4dbcb35fbf2e42c90897",
               "version_major": 2,
-              "version_minor": 0,
-              "model_id": "00c2e7114c4e4dbcb35fbf2e42c90897"
-            }
+              "version_minor": 0
+            },
+            "text/plain": [
+              "README.md:   0%|          | 0.00/4.84k [00:00<?, ?B/s]"
+            ]
           },
-          "metadata": {}
+          "metadata": {},
+          "output_type": "display_data"
         },
         {
-          "output_type": "display_data",
           "data": {
-            "text/plain": [
-              ".gitattributes:   0%|          | 0.00/1.52k [00:00<?, ?B/s]"
-            ],
             "application/vnd.jupyter.widget-view+json": {
+              "model_id": "5f554c8a330b4662bf54cd835869228c",
               "version_major": 2,
-              "version_minor": 0,
-              "model_id": "5f554c8a330b4662bf54cd835869228c"
-            }
+              "version_minor": 0
+            },
+            "text/plain": [
+              ".gitattributes:   0%|          | 0.00/1.52k [00:00<?, ?B/s]"
+            ]
           },
-          "metadata": {}
+          "metadata": {},
+          "output_type": "display_data"
         },
         {
-          "output_type": "display_data",
           "data": {
-            "text/plain": [
-              "pytorch_model.bin:   0%|          | 0.00/611M [00:00<?, ?B/s]"
-            ],
             "application/vnd.jupyter.widget-view+json": {
+              "model_id": "7ab3bf8c24db44e9955dcc77af36e4cd",
               "version_major": 2,
-              "version_minor": 0,
-              "model_id": "7ab3bf8c24db44e9955dcc77af36e4cd"
-            }
+              "version_minor": 0
+            },
+            "text/plain": [
+              "pytorch_model.bin:   0%|          | 0.00/611M [00:00<?, ?B/s]"
+            ]
           },
-          "metadata": {}
+          "metadata": {},
+          "output_type": "display_data"
         },
         {
-          "output_type": "display_data",
           "data": {
-            "text/plain": [
-              "tokenizer_config.json:   0%|          | 0.00/52.0 [00:00<?, ?B/s]"
-            ],
             "application/vnd.jupyter.widget-view+json": {
+              "model_id": "ff81e2a4b77d410f86e2734f307af0f8",
               "version_major": 2,
-              "version_minor": 0,
-              "model_id": "ff81e2a4b77d410f86e2734f307af0f8"
-            }
+              "version_minor": 0
+            },
+            "text/plain": [
+              "tokenizer_config.json:   0%|          | 0.00/52.0 [00:00<?, ?B/s]"
+            ]
           },
-          "metadata": {}
+          "metadata": {},
+          "output_type": "display_data"
         },
         {
-          "output_type": "stream",
           "name": "stderr",
+          "output_type": "stream",
           "text": [
             "/usr/local/lib/python3.10/dist-packages/huggingface_hub/file_download.py:1132: FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.\n",
             "  warnings.warn(\n"
           ]
         },
         {
-          "output_type": "display_data",
           "data": {
-            "text/plain": [
-              "config.json:   0%|          | 0.00/578 [00:00<?, ?B/s]"
-            ],
             "application/vnd.jupyter.widget-view+json": {
+              "model_id": "8c4411a7e9ef4a6981c46f9bba67d566",
               "version_major": 2,
-              "version_minor": 0,
-              "model_id": "8c4411a7e9ef4a6981c46f9bba67d566"
-            }
+              "version_minor": 0
+            },
+            "text/plain": [
+              "config.json:   0%|          | 0.00/578 [00:00<?, ?B/s]"
+            ]
           },
-          "metadata": {}
+          "metadata": {},
+          "output_type": "display_data"
         },
         {
-          "output_type": "display_data",
           "data": {
-            "text/plain": [
-              "spm.model:   0%|          | 0.00/2.46M [00:00<?, ?B/s]"
-            ],
             "application/vnd.jupyter.widget-view+json": {
+              "model_id": "8bbe3085ba76458583142659c02240dd",
               "version_major": 2,
-              "version_minor": 0,
-              "model_id": "8bbe3085ba76458583142659c02240dd"
-            }
+              "version_minor": 0
+            },
+            "text/plain": [
+              "spm.model:   0%|          | 0.00/2.46M [00:00<?, ?B/s]"
+            ]
           },
-          "metadata": {}
+          "metadata": {},
+          "output_type": "display_data"
         },
         {
-          "output_type": "stream",
           "name": "stderr",
+          "output_type": "stream",
           "text": [
             "/usr/local/lib/python3.10/dist-packages/transformers/convert_slow_tokenizer.py:560: UserWarning: The sentencepiece tokenizer that you are converting to a fast tokenizer uses the byte fallback option which is not implemented in the fast tokenizers. In practice this means that the fast version of the tokenizer can produce unknown tokens whereas the sentencepiece version would have converted these unknown tokens into a sequence of byte tokens matching the original piece of text.\n",
             "  warnings.warn(\n"
@@ -509,8 +514,8 @@
       },
       "outputs": [
         {
-          "output_type": "stream",
           "name": "stdout",
+          "output_type": "stream",
           "text": [
             "done\n"
           ]
@@ -550,7 +555,6 @@
         "    focal_loss_alpha=0.75,\n",
         "    focal_loss_gamma=2,\n",
         "    num_train_epochs=num_epochs,\n",
-        "    evaluation_strategy=\"steps\",\n",
         "    save_steps = 100,\n",
         "    save_total_limit=10,\n",
         "    dataloader_num_workers = 0,\n",
@@ -582,8 +586,8 @@
       },
       "outputs": [
         {
-          "output_type": "stream",
           "name": "stderr",
+          "output_type": "stream",
           "text": [
             "config.json not found in /content/models/checkpoint-100\n",
             "WARNING:huggingface_hub.hub_mixin:config.json not found in /content/models/checkpoint-100\n",
@@ -609,15 +613,15 @@
       },
       "outputs": [
         {
-          "output_type": "stream",
           "name": "stderr",
+          "output_type": "stream",
           "text": [
             "Asking to truncate to max_length but no maximum length is provided and the model has no predefined maximum length. Default to no truncation.\n"
           ]
         },
         {
-          "output_type": "stream",
           "name": "stdout",
+          "output_type": "stream",
           "text": [
             "Cristiano Ronaldo dos Santos Aveiro => Person\n",
             "Ballon d'Or => Award\n",
@@ -644,6 +648,11 @@
     }
   ],
   "metadata": {
+    "accelerator": "GPU",
+    "colab": {
+      "gpuType": "T4",
+      "provenance": []
+    },
     "kernelspec": {
       "display_name": "Python 3",
       "name": "python3"
@@ -661,17 +670,12 @@
       "version": "3.10.10"
     },
     "orig_nbformat": 4,
-    "colab": {
-      "provenance": [],
-      "gpuType": "T4"
-    },
-    "accelerator": "GPU",
     "widgets": {
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             "_model_module": "@jupyter-widgets/controls",
@@ -683,17 +687,64 @@
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-              "IPY_MODEL_12c1fe1e79644128870b20ddd6ac2b08"
+              "IPY_MODEL_b8b0c463a5ec4c5e83e3adbe424b5750",
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+              "IPY_MODEL_ed44b59f24224bd2ac9608505cbe54b4"
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-            "layout": "IPY_MODEL_aa722a17259542f1bc934fb578539260"
+            "layout": "IPY_MODEL_a01256737a80447aba5ffb0d6320177b"
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-        "fc5b3589df7a49349fe75079516e94b7": {
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+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
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+        "0f58dd3a6e1f4e25910f8412a3f937d3": {
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+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
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+        "11bd957d7a6a4f6dabb66dee38c29774": {
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+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
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+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
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-            "style": "IPY_MODEL_30d0d2fdf0874b6f93f9a1416af5cbc6",
-            "value": "Fetching 4 files: 100%"
+            "style": "IPY_MODEL_54dcc9bc81fc48b484cba6adf5000fcc",
+            "value": " 4/4 [00:05&lt;00:00,  1.32s/it]"
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