FIX Error in VLM fine-tuning notebook

In the notebook, get_peft_model(model) is called, which mutates the base
model. Then the same model is passed to SFTTrainer with a PEFT config,
which leads to another call to get_peft_model under the hood and thus to
PEFT being applied twice.

This fix removes the manual get_peft_model call and lets trl handle
this. We lose the ability to inspect the number of trainable parameters
but IMO this is the simplest solution.

Author: BenjaminBossan

notebooks/en/fine_tuning_vlm_trl.ipynb

@@ -607,7 +607,6 @@
     "    if 'model' in globals(): del globals()['model']\n",
     "    if 'processor' in globals(): del globals()['processor']\n",
     "    if 'trainer' in globals(): del globals()['trainer']\n",
-    "    if 'peft_model' in globals(): del globals()['peft_model']\n",
     "    if 'bnb_config' in globals(): del globals()['bnb_config']\n",
     "    time.sleep(2)\n",
     "\n",
@@ -738,17 +737,11 @@
     "id": "ITmkRHWCKYjf",
     "outputId": "49440aaf-89a4-4810-ad40-eafe4582bab3"
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "trainable params: 2,523,136 || all params: 8,293,898,752 || trainable%: 0.0304\n"
-     ]
+   "outputs": []
     }
    ],
    "source": [
-    "from peft import LoraConfig, get_peft_model\n",
+    "from peft import LoraConfig\n",
     "\n",
     "# Configure LoRA\n",
     "peft_config = LoraConfig(\n",
@@ -758,13 +751,7 @@
     "    bias=\"none\",\n",
     "    target_modules=[\"q_proj\", \"v_proj\"],\n",
     "    task_type=\"CAUSAL_LM\",\n",
-    ")\n",
-    "\n",
-    "# Apply PEFT model adaptation\n",
-    "peft_model = get_peft_model(model, peft_config)\n",
-    "\n",
-    "# Print trainable parameters\n",
-    "peft_model.print_trainable_parameters()"
+    ")"
    ]
   },
   {

notebooks/zh-CN/fine_tuning_vlm_trl.ipynb

@@ -1120,7 +1120,6 @@
         "    if 'model' in globals(): del globals()['model']\n",
         "    if 'processor' in globals(): del globals()['processor']\n",
         "    if 'trainer' in globals(): del globals()['trainer']\n",
-        "    if 'peft_model' in globals(): del globals()['peft_model']\n",
         "    if 'bnb_config' in globals(): del globals()['bnb_config']\n",
         "    time.sleep(2)\n",
         "\n",
@@ -1243,17 +1242,9 @@
         "id": "ITmkRHWCKYjf",
         "outputId": "3ca824c9-4aca-4d5b-e942-7a1705939e08"
       },
-      "outputs": [
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "trainable params: 2,523,136 || all params: 8,293,898,752 || trainable%: 0.0304\n"
-          ]
-        }
-      ],
+      "outputs": [],
       "source": [
-        "from peft import LoraConfig, get_peft_model\n",
+        "from peft import LoraConfig\n",
         "\n",
         "# Configure LoRA\n",
         "peft_config = LoraConfig(\n",
@@ -1263,13 +1254,7 @@
         "    bias=\"none\",\n",
         "    target_modules=[\"q_proj\", \"v_proj\"],\n",
         "    task_type=\"CAUSAL_LM\",\n",
-        ")\n",
-        "\n",
-        "# Apply PEFT model adaptation\n",
-        "peft_model = get_peft_model(model, peft_config)\n",
-        "\n",
-        "# Print trainable parameters\n",
-        "peft_model.print_trainable_parameters()"
+        ")"
       ]
     },
     {