diff --git a/TD2 Deep Learning.ipynb b/TD2 Deep Learning.ipynb
index b7f56959780244b8f89b795c0c63c1b7f245a609..0d885ba0ab374708c5bc09d9ab8472c6c18eee8e 100644
--- a/TD2 Deep Learning.ipynb	
+++ b/TD2 Deep Learning.ipynb	
@@ -23769,12 +23769,20 @@
     "print_size_of_model(model, \"fp32\")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "d1fc547c",
+   "metadata": {},
+   "source": [
+    "### La taille du modèle 1 initial est de 251.278 KB"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "05c4e9ad",
    "metadata": {},
    "source": [
-    "Post training quantization example"
+    "### On va compresser ce modèle : "
    ]
   },
   {
@@ -23804,11 +23812,18 @@
    "source": [
     "import torch.quantization\n",
     "\n",
-    "\n",
     "quantized_model = torch.quantization.quantize_dynamic(model, dtype=torch.qint8)\n",
     "print_size_of_model(quantized_model, \"int8\")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "70bd3046",
+   "metadata": {},
+   "source": [
+    "### Le modèle compressé a une taille de 76.522 KB. Il y a donc eu une réduction de 174.756 KB."
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 19,
@@ -23897,6 +23912,20 @@
     ")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "50c95c3e",
+   "metadata": {},
+   "source": [
+    "### En terme de précision, elle est la même en pourcentage pour presque toutes les classes (en comparaison avec le modèle non compressé).\n",
+    "\n",
+    "#### Elle difére de 1% pour la classe horse.\n",
+    "\n",
+    "### Au global, la précision est la même.\n",
+    "\n",
+    "### Le modèle compressé conserve la précision du modèle tout en réduisant sa taille."
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "7b108e17",
@@ -23913,6 +23942,14 @@
     "Try training aware quantization to mitigate the impact on the accuracy (doc available here https://pytorch.org/docs/stable/quantization.html#torch.quantization.quantize_dynamic)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "a5ba7855",
+   "metadata": {},
+   "source": [
+    "### On va essayer le training aware quantization"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "201470f9",
diff --git a/hymenoptera_data/test/ants/.ants-devouring-remains-of-large-dead-insect-on-red-tile-in-Stellenbosch-South-Africa-closeup-1-DHD.jpg.icloud b/hymenoptera_data/test/ants/.ants-devouring-remains-of-large-dead-insect-on-red-tile-in-Stellenbosch-South-Africa-closeup-1-DHD.jpg.icloud
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