updating notebook to confirm fix

Signed-off-by: GiulioZizzo <[email protected]>

Author: GiulioZizzo

notebooks/huggingface_notebook.ipynb

@@ -34,7 +34,9 @@
     "\n",
     "import numpy as np\n",
     "from torchvision import datasets\n",
-    "from art.estimators.classification.hugging_face import HuggingFaceClassifierPyTorch"
+    "from art.estimators.classification.hugging_face import HuggingFaceClassifierPyTorch\n",
+    "\n",
+    "device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')"
    ]
   },
   {
@@ -86,7 +88,7 @@
     "    model = transformers.AutoModelForImageClassification.from_pretrained(architecture,\n",
     "                                                                         ignore_mismatched_sizes=True,\n",
     "                                                                         num_labels=10)\n",
-    "\n",
+    "    model = model.to(device)\n",
     "    # The HuggingFaceClassifierPyTorch follows broadly the same API as the PyTorchClassifier\n",
     "    # So we can supply the loss function, the input shape of the data we will supply, the optimizer, etc.\n",
     "    # Note, frequently we will be performing fine-tuning or transfer learning with vision transformners and \n",
@@ -533,6 +535,7 @@
     "    import timm\n",
     "    \n",
     "    model = timm.create_model('resnet50.a1_in1k', pretrained=True)\n",
+    "    model = model.to(device)\n",
     "    upsampler = torch.nn.Upsample(scale_factor=7, mode='nearest')\n",
     "    \n",
     "    optimizer = Adam(model.parameters(), lr=1e-3)\n",
@@ -816,7 +819,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.3"
+   "version": "3.8.10"
   }
  },
  "nbformat": 4,