Upload transformers_example_mt.ipynb

transformers_example_mt.ipynb

@@ -29,27 +29,18 @@
    "execution_count": 2,
    "id": "ba9ec6c7",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Some weights of BertModel were not initialized from the model checkpoint at mdbr-leaf-mt and are newly initialized: ['pooler.dense.bias', 'pooler.dense.weight']\n",
-      "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# Then load it\n",
     "MODEL = \"mdbr-leaf-mt\"\n",
     "\n",
     "tokenizer = AutoTokenizer.from_pretrained(MODEL)\n",
-    "model = AutoModel.from_pretrained(MODEL)"
+    "model = AutoModel.from_pretrained(MODEL, add_pooling_layer=False)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "id": "ebaf1a76",
    "metadata": {},
    "outputs": [],
@@ -62,7 +53,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": null,
    "id": "03ffcd9c",
    "metadata": {},
    "outputs": [
@@ -130,8 +121,8 @@
     "print(f\"Similarities:\\n{similarities}\")\n",
     "\n",
     "# Similarities:\n",
-    "#  tensor([[0.6857, 0.4598],\n",
-    "#          [0.4238, 0.5723]])"
+    "# tensor([[0.9063, 0.7287],\n",
+    "#         [0.6725, 0.8287]])"
    ]
   },
   {