Mode advanced data exploration and notebook htmls

notebooks/03_semantic_methods.ipynb

@@ -13,7 +13,8 @@
    "outputs": [],
    "source": [
     "import spacy\n",
-    "nlp =  spacy.load(\"en_core_web_lg\") # Medium model"
+    "nlp = spacy.load(\"en_core_web_lg\")          # Large model\n",
+    "nlp_trf =  spacy.load(\"en_core_web_trf\")    # Transformer Model"
    ]
   },
   {
@@ -26,7 +27,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 2,
    "id": "8a3c4314a90086fe",
    "metadata": {
     "ExecuteTime": {
@@ -36,17 +37,39 @@
    },
    "outputs": [
     {
-     "ename": "ValueError",
-     "evalue": "[E010] Word vectors set to length 0. This may be because you don't have a model installed or loaded, or because your model doesn't include word vectors. For more info, see the docs:\nhttps://spacy.io/usage/models",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[31m---------------------------------------------------------------------------\u001b[39m",
-      "\u001b[31mValueError\u001b[39m                                Traceback (most recent call last)",
-      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[9]\u001b[39m\u001b[32m, line 9\u001b[39m\n\u001b[32m      7\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m word2 \u001b[38;5;129;01min\u001b[39;00m words:\n\u001b[32m      8\u001b[39m     \u001b[38;5;28;01mif\u001b[39;00m word1 != word2:\n\u001b[32m----> \u001b[39m\u001b[32m9\u001b[39m         similarity = \u001b[43mnlp\u001b[49m\u001b[43m.\u001b[49m\u001b[43mvocab\u001b[49m\u001b[43m[\u001b[49m\u001b[43mword1\u001b[49m\u001b[43m]\u001b[49m\u001b[43m.\u001b[49m\u001b[43msimilarity\u001b[49m\u001b[43m(\u001b[49m\u001b[43mnlp\u001b[49m\u001b[43m.\u001b[49m\u001b[43mvocab\u001b[49m\u001b[43m[\u001b[49m\u001b[43mword2\u001b[49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m     10\u001b[39m         \u001b[38;5;28mprint\u001b[39m(\u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mword1\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m - \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mword2\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00msimilarity\u001b[38;5;132;01m:\u001b[39;00m\u001b[33m.3f\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m\"\u001b[39m)\n",
-      "\u001b[36mFile \u001b[39m\u001b[32m~/code/plagiarism-detector/.venv/lib/python3.13/site-packages/spacy/lexeme.pyx:146\u001b[39m, in \u001b[36mspacy.lexeme.Lexeme.similarity\u001b[39m\u001b[34m()\u001b[39m\n",
-      "\u001b[36mFile \u001b[39m\u001b[32m~/code/plagiarism-detector/.venv/lib/python3.13/site-packages/spacy/lexeme.pyx:164\u001b[39m, in \u001b[36mspacy.lexeme.Lexeme.vector_norm.__get__\u001b[39m\u001b[34m()\u001b[39m\n",
-      "\u001b[36mFile \u001b[39m\u001b[32m~/code/plagiarism-detector/.venv/lib/python3.13/site-packages/spacy/lexeme.pyx:176\u001b[39m, in \u001b[36mspacy.lexeme.Lexeme.vector.__get__\u001b[39m\u001b[34m()\u001b[39m\n",
-      "\u001b[31mValueError\u001b[39m: [E010] Word vectors set to length 0. This may be because you don't have a model installed or loaded, or because your model doesn't include word vectors. For more info, see the docs:\nhttps://spacy.io/usage/models"
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "cat - dog: 0.802\n",
+      "cat - feline: 0.699\n",
+      "cat - feral: 0.486\n",
+      "cat - vehicle: 0.190\n",
+      "cat - car: 0.319\n",
+      "dog - cat: 0.802\n",
+      "dog - feline: 0.566\n",
+      "dog - feral: 0.400\n",
+      "dog - vehicle: 0.258\n",
+      "dog - car: 0.356\n",
+      "feline - cat: 0.699\n",
+      "feline - dog: 0.566\n",
+      "feline - feral: 0.543\n",
+      "feline - vehicle: 0.103\n",
+      "feline - car: 0.095\n",
+      "feral - cat: 0.486\n",
+      "feral - dog: 0.400\n",
+      "feral - feline: 0.543\n",
+      "feral - vehicle: 0.088\n",
+      "feral - car: 0.040\n",
+      "vehicle - cat: 0.190\n",
+      "vehicle - dog: 0.258\n",
+      "vehicle - feline: 0.103\n",
+      "vehicle - feral: 0.088\n",
+      "vehicle - car: 0.767\n",
+      "car - cat: 0.319\n",
+      "car - dog: 0.356\n",
+      "car - feline: 0.095\n",
+      "car - feral: 0.040\n",
+      "car - vehicle: 0.767\n"
      ]
     }
    ],
@@ -115,7 +138,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "id": "c100956f89d9b581",
    "metadata": {},
    "outputs": [],