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            "Collecting transformers\n",
            "  Downloading transformers-4.35.0-py3-none-any.whl (7.9 MB)\n",
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            "Collecting tokenizers<0.15,>=0.14 (from transformers)\n",
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            "\u001b[?25hCollecting safetensors>=0.3.1 (from transformers)\n",
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            "Installing collected packages: safetensors, huggingface-hub, tokenizers, transformers\n",
            "Successfully installed huggingface-hub-0.17.3 safetensors-0.4.0 tokenizers-0.14.1 transformers-4.35.0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!huggingface-cli login\n",
        "#from huggingface_hub import notebook_login\n",
        "#notebook_login()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 509,
          "referenced_widgets": [
            "afb4cf60647746cea3e1ef02bd4637fb",
            "0645cea30b14400aa891ef4223c0e52d",
            "80633cc88f124faf8f4aa3dc2c5d8550",
            "3a632a25760f4fbbbba8078825084a55",
            "f9c6c58d612447eab1af89ec963afa9e",
            "12a3006fa511479d802c869977087f08",
            "2b7db7372ba64aa899516acad2df2cca",
            "e4ef40a5fe904eeea29938f2b399521f",
            "58f4807b08fc4e4ca6eed3d266c2990e",
            "614d8f9b2a684344a6308886d6a6a965",
            "7ea45a099d7d4f89aa221426b0b31738",
            "80a77d6070284a5a88a42c1f7ae9438d",
            "6f2700e5f2f549978717c117122b77b4",
            "3fb30bbe0b4f445992638460afab6542",
            "72a2c3784981458f9279b3e817ac2f66",
            "f9fbc0bca2434a468eb561531e070807",
            "87800c464d694f5a953b4ea27b8eccab",
            "fd2fd0d53cd24e0cabf6478529ebd794",
            "9a42ecb77a184287ab35ff44c1da21df",
            "f998e7f3df9d42c7953f288bc3fd039a",
            "343c47eaccd249c8a797b2c1378603c5",
            "aba32fb028f447ee91c74092b14e494f",
            "59901c4463764d719fc799e52c91a07a",
            "7d591e5027c54034a51ae0ffc6fbb9c3",
            "7efa196b0c24409d8ee0b23ad303f653",
            "9f7f6ce9ee854d65827321123c82b9f6",
            "7afcba778e9048a29044aaf01aec7ca2",
            "ab0c301db6104a37abb4051f9f90a896",
            "eb262072aa73425ba9bc5324f5920665",
            "c475ac1a2f904d038944cb7e4a65812e",
            "e1af2b8270ca43aa9c9b0f7f4acd5300",
            "cd7b4ce4f200489cbfbf0174b0561511"
          ]
        },
        "id": "4PwffMXrLsVy",
        "outputId": "16bf648d-2275-40b0-c1db-fee21ee94699"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "    _|    _|  _|    _|    _|_|_|    _|_|_|  _|_|_|  _|      _|    _|_|_|      _|_|_|_|    _|_|      _|_|_|  _|_|_|_|\n",
            "    _|    _|  _|    _|  _|        _|          _|    _|_|    _|  _|            _|        _|    _|  _|        _|\n",
            "    _|_|_|_|  _|    _|  _|  _|_|  _|  _|_|    _|    _|  _|  _|  _|  _|_|      _|_|_|    _|_|_|_|  _|        _|_|_|\n",
            "    _|    _|  _|    _|  _|    _|  _|    _|    _|    _|    _|_|  _|    _|      _|        _|    _|  _|        _|\n",
            "    _|    _|    _|_|      _|_|_|    _|_|_|  _|_|_|  _|      _|    _|_|_|      _|        _|    _|    _|_|_|  _|_|_|_|\n",
            "    \n",
            "    To login, `huggingface_hub` requires a token generated from https://huggingface.co/settings/tokens .\n",
            "Token: \n",
            "Add token as git credential? (Y/n) y\n",
            "Token is valid (permission: write).\n",
            "\u001b[1m\u001b[31mCannot authenticate through git-credential as no helper is defined on your machine.\n",
            "You might have to re-authenticate when pushing to the Hugging Face Hub.\n",
            "Run the following command in your terminal in case you want to set the 'store' credential helper as default.\n",
            "\n",
            "git config --global credential.helper store\n",
            "\n",
            "Read https://git-scm.com/book/en/v2/Git-Tools-Credential-Storage for more details.\u001b[0m\n",
            "Token has not been saved to git credential helper.\n",
            "Your token has been saved to /root/.cache/huggingface/token\n",
            "Login successful\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "VBox(children=(HTML(value='<center> <img\\nsrc=https://huggingface.co/front/assets/huggingface_logo-noborder.sv…"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "afb4cf60647746cea3e1ef02bd4637fb"
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 101,
          "referenced_widgets": [
            "7ed17347ad114ee6a3f5bbe44547458e",
            "c25700be00a04f41b6792c9a3e75cffc",
            "fa3fb7b518bf4d4f8b1201d16fe0767f",
            "9ff4dbe4ff744d2aae82de08feead57f",
            "15c7a3f8f13d4812a436fe6ea3fb7573",
            "895122e40b324be1aae88771173ac719",
            "bb72a3986e8d4dd2a551cdcada837881",
            "8dd8f7deb5d64e80b30e348470ec21e6",
            "c63216e05f8547ce9682b8570b954252",
            "c5b57f3fa4b847baa7548ce653d9aaa2",
            "b465c6b89cc74a358d7b0aff13d5c058"
          ]
        },
        "id": "vnRfcWYuJFSd",
        "outputId": "e662c39e-f5a9-412e-b9cc-632baed6b263"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "config.json not found in HuggingFace Hub.\n",
            "WARNING:huggingface_hub.hub_mixin:config.json not found in HuggingFace Hub.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Fetching 8 files:   0%|          | 0/8 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "7ed17347ad114ee6a3f5bbe44547458e"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "WARNING:tensorflow:No training configuration found in save file, so the model was *not* compiled. Compile it manually.\n"
          ]
        }
      ],
      "source": [
        "from huggingface_hub import from_pretrained_keras\n",
        "\n",
        "model = from_pretrained_keras(\"mabzak/lstm-id-yt-comment\")"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from tensorflow.keras.preprocessing.text import Tokenizer\n",
        "import pandas as pd\n",
        "from keras.preprocessing.text import Tokenizer\n",
        "from tensorflow.keras.preprocessing.sequence import pad_sequences"
      ],
      "metadata": {
        "id": "ASQghJpLYx_I"
      },
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Gantilah 'comments.csv' dengan nama file CSV yang sesuai\n",
        "df = pd.read_csv('https://huggingface.co/datasets/mabzak/indonesia-youtube-comment/raw/main/comment1.csv')\n",
        "texts = df['text']\n",
        "\n",
        "# Membuang baris dengan nilai teks yang hilang\n",
        "texts = texts.dropna()\n",
        "\n",
        "# Tokenisasi dan pembuatan representasi numerik dari kata-kata\n",
        "tokenizer = Tokenizer()\n",
        "tokenizer.fit_on_texts(texts)\n",
        "total_words = len(tokenizer.word_index) + 1"
      ],
      "metadata": {
        "id": "JRJ2mLn4XQcM"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "tokenizer"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7S_MvtZAb3nr",
        "outputId": "e3262896-35df-4f40-dbba-571c46349dd9"
      },
      "execution_count": 64,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<keras.src.preprocessing.text.Tokenizer at 0x7d12a85ebe80>"
            ]
          },
          "metadata": {},
          "execution_count": 64
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "input_sequences = []\n",
        "for line in texts:\n",
        "    token_list = tokenizer.texts_to_sequences([line])[0]\n",
        "    for i in range(1, len(token_list)):\n",
        "        n_gram_sequence = token_list[:i+1]\n",
        "        input_sequences.append(n_gram_sequence)\n",
        "\n",
        "max_sequence_length = max([len(x) for x in input_sequences])\n",
        "input_sequences = pad_sequences(input_sequences, maxlen=max_sequence_length, padding='pre')\n",
        "predictors, label = input_sequences[:, :-1], input_sequences[:, -1]"
      ],
      "metadata": {
        "id": "PZC9THPtWHx7"
      },
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "\n",
        "def predict_next_sentence(seed_text, model, tokenizer, max_sequence_length, num_words):\n",
        "    generated_sentence = seed_text\n",
        "\n",
        "    for _ in range(num_words):\n",
        "        token_list = tokenizer.texts_to_sequences([generated_sentence])[0]\n",
        "        token_list = pad_sequences([token_list], maxlen=max_sequence_length-1, padding='pre')\n",
        "        predicted_probs = model.predict(token_list, verbose=0)[0]\n",
        "        predicted_index = np.argmax(predicted_probs)\n",
        "\n",
        "        # Temukan kata yang sesuai dengan indeks prediksi\n",
        "        output_word = \"\"\n",
        "        for word, index in tokenizer.word_index.items():\n",
        "            if index == predicted_index:\n",
        "                output_word = word\n",
        "                break\n",
        "\n",
        "        # Tambahkan kata ke kalimat yang dihasilkan\n",
        "        generated_sentence += \" \" + output_word\n",
        "\n",
        "    return generated_sentence\n"
      ],
      "metadata": {
        "id": "JfUx3ItpV1k_"
      },
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Menggunakan seed text untuk memprediksi kalimat berikutnya\n",
        "seed_text = \"masa depan negara\"\n",
        "predicted_sentence = predict_next_sentence(seed_text, model, tokenizer, max_sequence_length, num_words=10)\n",
        "print(\"Kalimat yang Diprediksi:\", predicted_sentence)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qcO83u2fVsKE",
        "outputId": "cbfebba6-ceb1-4bb0-d76d-305ce3491287"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Kalimat yang Diprediksi: masa depan negara ini saya yakin bisa di pimpin oleh orang yg baik\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "\n",
        "---\n",
        "\n"
      ],
      "metadata": {
        "id": "sGs-qtsIltSr"
      }
    }
  ]
}