adding code

blender_bot.ipynb

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+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "name": "blender-agent.ipynb",
+      "private_outputs": true,
+      "provenance": [],
+      "collapsed_sections": []
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    },
+    "accelerator": "GPU"
+  },
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "rJ-QA0ODU4x9"
+      },
+      "source": [
+        "# Install Dependancies"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "Bx20ocfPWAYS"
+      },
+      "source": [
+        "#install pytorch\n",
+        "!pip3 install torch==1.9.1+cu111 torchvision==0.10.1+cu111 torchaudio===0.9.1 -f https://download.pytorch.org/whl/torch_stable.html"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "UcY5FPNHY72K"
+      },
+      "source": [
+        "#install transformers\n",
+        "!pip install transformers"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "DKilCO-TU_s0"
+      },
+      "source": [
+        "# Import Model"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "VU33RjeOc8eG"
+      },
+      "source": [
+        "#import model class and tokenizer\n",
+        "from transformers import BlenderbotTokenizer, BlenderbotForConditionalGeneration"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "6LZEzJXpc8pg"
+      },
+      "source": [
+        "#download and setup the model and tokenizer\n",
+        "model_name = 'facebook/blenderbot-400M-distill'\n",
+        "tokenizer = BlenderbotTokenizer.from_pretrained(model_name)\n",
+        "model = BlenderbotForConditionalGeneration.from_pretrained(model_name)"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "_T9nRG5eVENY"
+      },
+      "source": [
+        "# make conversation"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "AkrWBF3af8Ns"
+      },
+      "source": [
+        "#making an utterance \n",
+        "utterance = \"My name is gold, I like football and coding\""
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "JDDDJ2V3f8QT"
+      },
+      "source": [
+        "#tokenize the utterance\n",
+        "inputs = tokenizer(utterance, return_tensors=\"pt\")\n",
+        "inputs"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "-QYclYycf8TN"
+      },
+      "source": [
+        "#generate model results\n",
+        "result = model.generate(**inputs)\n",
+        "result"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "syB3F_iyf8Vt"
+      },
+      "source": [
+        "tokenizer.decode(result[0])"
+      ],
+      "execution_count": null,
+      "outputs": []
+    }
+  ]
+}

requirements.txt

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+transformers
+gradio
+torch