Colab notebook

you can use this in your own virtual enviroment

Sentence_Generation.ipynb

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+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "provenance": []
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": 18,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "yqiXEj_uL8kv",
+        "outputId": "b3591701-bb63-4496-f90d-50d958b32b32"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
+            "  Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
+            "  Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n"
+          ]
+        }
+      ],
+      "source": [
+        "!pip install -q gradio\n",
+        "!pip install -q git+https://github.com/huggingface/transformers.git\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "import gradio as gr\n",
+        "import tensorflow as tf\n",
+        "from transformers import TFGPT2LMHeadModel,GPT2Tokenizer"
+      ],
+      "metadata": {
+        "id": "NWyCNUJIMp58"
+      },
+      "execution_count": 19,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "tokenizer = GPT2Tokenizer.from_pretrained (\"gpt2\")\n",
+        "model = TFGPT2LMHeadModel.from_pretrained (\"gpt2\" ,pad_token_id=tokenizer.eos_token_id)"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "uGE4z27oMuZx",
+        "outputId": "a26407d4-2628-44d4-be16-f3826a043eb8"
+      },
+      "execution_count": 10,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "All PyTorch model weights were used when initializing TFGPT2LMHeadModel.\n",
+            "\n",
+            "All the weights of TFGPT2LMHeadModel were initialized from the PyTorch model.\n",
+            "If your task is similar to the task the model of the checkpoint was trained on, you can already use TFGPT2LMHeadModel for predictions without further training.\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "def generate_text(input_Prompt):\n",
+        "    input_ids = tokenizer.encode(input_Prompt, return_tensors='tf')\n",
+        "    beam_output = model.generate(input_ids, max_length=100, num_beams=5, no_repeat_ngram_size=2, early_stopping=False)\n",
+        "    output = tokenizer.decode(beam_output[0], skip_special_tokens=True, clean_up_tokenization_spaces=True)\n",
+        "    return \".\".join(output.split(\".\")[:-1]) + \".\"\n"
+      ],
+      "metadata": {
+        "id": "hoKSOw9eMvQt"
+      },
+      "execution_count": 16,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "output_text = gr.Textbox()\n",
+        "\n",
+        "gr. Interface(generate_text,\"textbox\", output_text, title=\"GPT-2\",\n",
+        "\n",
+        "description=\"OpenAI's GPT-2 is an unsupervised language model that \\ can generate coherent text. Go ahead and input a sentence and see what it completes \\ it with! Takes around 20s to run.\").launch()"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 648
+        },
+        "id": "cM-5NqQ-M1dn",
+        "outputId": "c52b7b5d-43b1-4bc7-aebe-761ddb8be371"
+      },
+      "execution_count": 17,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Setting queue=True in a Colab notebook requires sharing enabled. Setting `share=True` (you can turn this off by setting `share=False` in `launch()` explicitly).\n",
+            "\n",
+            "Colab notebook detected. To show errors in colab notebook, set debug=True in launch()\n",
+            "Running on public URL: https://ac6c205dbfaa7333aa.gradio.live\n",
+            "\n",
+            "This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces)\n"
+          ]
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ],
+            "text/html": [
+              "<div><iframe src=\"https://ac6c205dbfaa7333aa.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
+            ]
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": []
+          },
+          "metadata": {},
+          "execution_count": 17
+        }
+      ]
+    }
+  ]
+}