LLama2.ipynb

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  },
  "cells": [
    {
      "cell_type": "code",
      "source": [
        "! nvidia-smi"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "id": "_CuxLPF_XP32",
        "outputId": "4d4cfc62-31ff-4ad9-f88a-81efb8869db8"
      },
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Sun Jul 23 11:10:34 2023       \n",
            "+-----------------------------------------------------------------------------+\n",
            "| NVIDIA-SMI 525.105.17   Driver Version: 525.105.17   CUDA Version: 12.0     |\n",
            "|-------------------------------+----------------------+----------------------+\n",
            "| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |\n",
            "| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |\n",
            "|                               |                      |               MIG M. |\n",
            "|===============================+======================+======================|\n",
            "|   0  NVIDIA A100-SXM...  Off  | 00000000:00:04.0 Off |                    0 |\n",
            "| N/A   31C    P0    47W / 400W |      0MiB / 40960MiB |      0%      Default |\n",
            "|                               |                      |             Disabled |\n",
            "+-------------------------------+----------------------+----------------------+\n",
            "                                                                               \n",
            "+-----------------------------------------------------------------------------+\n",
            "| Processes:                                                                  |\n",
            "|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |\n",
            "|        ID   ID                                                   Usage      |\n",
            "|=============================================================================|\n",
            "|  No running processes found                                                 |\n",
            "+-----------------------------------------------------------------------------+\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "! pip install huggingface_hub"
      ],
      "metadata": {
        "id": "NBDA6YUncb71"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!huggingface-cli login"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "id": "NsdBPrMvcfLI",
        "outputId": "9e097215-4a97-4223-fe9f-6e8fdbbad221"
      },
      "execution_count": 3,
      "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: Traceback (most recent call last):\n",
            "  File \"/usr/lib/python3.10/getpass.py\", line 77, in unix_getpass\n",
            "    passwd = _raw_input(prompt, stream, input=input)\n",
            "  File \"/usr/lib/python3.10/getpass.py\", line 146, in _raw_input\n",
            "    line = input.readline()\n",
            "KeyboardInterrupt\n",
            "\n",
            "During handling of the above exception, another exception occurred:\n",
            "\n",
            "Traceback (most recent call last):\n",
            "  File \"/usr/local/bin/huggingface-cli\", line 8, in <module>\n",
            "    sys.exit(main())\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/huggingface_hub/commands/huggingface_cli.py\", line 45, in main\n",
            "    service.run()\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/huggingface_hub/commands/user.py\", line 101, in run\n",
            "    login(token=self.args.token, add_to_git_credential=self.args.add_to_git_credential)\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/huggingface_hub/_login.py\", line 100, in login\n",
            "    interpreter_login(new_session=new_session, write_permission=write_permission)\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/huggingface_hub/_login.py\", line 161, in interpreter_login\n",
            "    token = getpass(\"Token: \")\n",
            "  File \"/usr/lib/python3.10/getpass.py\", line 45, in unix_getpass\n",
            "    with contextlib.ExitStack() as stack:\n",
            "  File \"/usr/lib/python3.10/contextlib.py\", line 538, in __exit__\n",
            "    frame_exc = sys.exc_info()[1]\n",
            "KeyboardInterrupt\n",
            "^C\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "! pip install transformers sentencepiece"
      ],
      "metadata": {
        "id": "xwgrlpfmcjKX"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import torch"
      ],
      "metadata": {
        "id": "x-gKWAz2c9ws"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer\n",
        "model_path = \"daryl149/llama-2-7b-chat-hf\"\n",
        "model = AutoModelForCausalLM.from_pretrained(model_path).cuda()"
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      "execution_count": 6,
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        {
          "output_type": "display_data",
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            "text/plain": [
              "Downloading (…)lve/main/config.json:   0%|          | 0.00/507 [00:00<?, ?B/s]"
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        {
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              "Downloading (…)l-00002-of-00002.bin:   0%|          | 0.00/3.50G [00:00<?, ?B/s]"
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        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Loading checkpoint shards:   0%|          | 0/2 [00:00<?, ?it/s]"
            ],
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        {
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        "id": "aRzjMzJvdx9l",
        "outputId": "899e5680-0c29-4f2f-9d59-7cec37deccd4"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)okenizer_config.json:   0%|          | 0.00/727 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading tokenizer.model:   0%|          | 0.00/500k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
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          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)cial_tokens_map.json:   0%|          | 0.00/411 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
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          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "You are using the legacy behaviour of the <class 'transformers.models.llama.tokenization_llama.LlamaTokenizer'>. This means that tokens that come after special tokens will not be properly handled. We recommend you to read the related pull request available at https://github.com/huggingface/transformers/pull/24565\n"
          ]
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      ]
    },
    {
      "cell_type": "code",
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        "streamer = TextStreamer(tokenizer, skip_prompt = True, skip_special_tokens = True)"
      ],
      "metadata": {
        "id": "Y5zsizpcecxD"
      },
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "prompt = \"How to make money on the internet?\"\n",
        "generated_ids = model.generate(tokenizer(prompt, return_tensors = 'pt').input_ids.cuda(), max_new_tokens = 1000, streamer = streamer)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
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            "\n",
            "\n",
            "There are many ways to make money on the internet, including:\n",
            "\n",
            "1. Affiliate marketing: Promote products or services of other companies and earn a commission for each sale made through your unique referral link.\n",
            "2. Online tutoring or teaching: Offer your expertise and teach others a skill or subject via online platforms such as Udemy, Teachable, or TutorMe.\n",
            "3. Creating and selling digital products: Sell e-books, printables, templates, or other digital products through your own website or platforms like Etsy or Gumroad.\n",
            "4. Blogging: Create a blog and monetize it through advertising, sponsored posts, or affiliate marketing.\n",
            "5. Dropshipping: Sell products without holding any inventory, by partnering with a supplier that ships products directly to customers.\n",
            "6. Online freelancing: Offer your skills such as writing, graphic design, web development, or social media management on freelancing platforms like Upwork, Fiverr, or Freelancer.\n",
            "7. Creating and selling an online course: Create a course on a topic you are knowledgeable about and sell it on platforms like Udemy, Teachable, or Skillshare.\n",
            "8. Stock photography: Sell your photos on stock photo websites like Shutterstock, iStock, or Adobe Stock.\n",
            "9. Online surveys: Participate in online surveys and earn rewards or cash through websites like Swagbucks, Survey Junkie, or Vindale Research.\n",
            "10. Creating and selling a mobile app or game: Develop a mobile app or game and sell it on app stores like Apple App Store or Google Play.\n",
            "It's important to note that making money on the internet requires effort, patience, and persistence. It's also important to be aware of the potential scams and to always research the opportunities thoroughly before investing your time or money.\n"
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