move model to examples

      "provenance": [],

      "collapsed_sections": [],

      "mount_file_id": "1pD0fsKpYujJgNAttRn9vkdBYGpwCeVC0",

      "authorship_tag": "ABX9TyOqfnobS4p9ovUKCyQSOUah",

      "authorship_tag": "ABX9TyMJH1b/1u2aqHd0X0XV7QrO",

      "include_colab_link": true

    },

    "kernelspec": {

        "from transformers import RobertaModel, RobertaTokenizer\n",

        "from bertviz import head_view\n",

        "\n",

        "model_version = 'seyonec/ChemBERTa-zinc250k-v1'\n",

        "model_version = 'seyonec/ChemBERTa_zinc250k_v2_40k'\n",

        "model = RobertaModel.from_pretrained(model_version, output_attentions=True)\n",

        "tokenizer = RobertaTokenizer.from_pretrained(model_version)\n",

        "\n",

        "outputId": "54a36a91-4b6c-4987-fb69-b2610d0d3286"

      },

      "source": [

        "model = ClassificationModel('roberta', 'seyonec/ChemBERTa-zinc-base-v1', args={'num_train_epochs': 3, 'auto_weights': True}) # You can set class weights by using the optional weight argument\n"

        "model = ClassificationModel('roberta', 'seyonec/ChemBERTa_zinc250k_v2_40k', args={'num_train_epochs': 3, 'auto_weights': True}) # You can set class weights by using the optional weight argument\n"

      ],

      "execution_count": null,

      "outputs": [