Code_Llama_7B_instruct.ipynb

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  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "#### Notes for using this note\n",
        "* first install accelerate then restart the kernel --> this step is very important\n",
        "* second after restarting the kernel install transformers library then load the libraries\n"
      ],
      "metadata": {
        "id": "HMq-UlW5GxjX"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install accelerate"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DWiZtjPs8mEa",
        "outputId": "8eb387b8-a0b5-49c3-f6f5-6d967938868f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: accelerate in /usr/local/lib/python3.10/dist-packages (0.22.0)\n",
            "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from accelerate) (1.23.5)\n",
            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from accelerate) (23.1)\n",
            "Requirement already satisfied: psutil in /usr/local/lib/python3.10/dist-packages (from accelerate) (5.9.5)\n",
            "Requirement already satisfied: pyyaml in /usr/local/lib/python3.10/dist-packages (from accelerate) (6.0.1)\n",
            "Requirement already satisfied: torch>=1.10.0 in /usr/local/lib/python3.10/dist-packages (from accelerate) (2.0.1+cu118)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (3.12.2)\n",
            "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (4.7.1)\n",
            "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (1.12)\n",
            "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (3.1)\n",
            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (3.1.2)\n",
            "Requirement already satisfied: triton==2.0.0 in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (2.0.0)\n",
            "Requirement already satisfied: cmake in /usr/local/lib/python3.10/dist-packages (from triton==2.0.0->torch>=1.10.0->accelerate) (3.27.2)\n",
            "Requirement already satisfied: lit in /usr/local/lib/python3.10/dist-packages (from triton==2.0.0->torch>=1.10.0->accelerate) (16.0.6)\n",
            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch>=1.10.0->accelerate) (2.1.3)\n",
            "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch>=1.10.0->accelerate) (1.3.0)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install git+https://github.com/huggingface/transformers.git@refs/pull/25740/head accelerate"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "p2vuAVwC8V2p",
        "outputId": "75e1b605-f537-4bb5-e39f-b8f63f2ffdef"
      },
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting git+https://github.com/huggingface/transformers.git@refs/pull/25740/head\n",
            "  Cloning https://github.com/huggingface/transformers.git (to revision refs/pull/25740/head) to /tmp/pip-req-build-g37cakmf\n",
            "  Running command git clone --filter=blob:none --quiet https://github.com/huggingface/transformers.git /tmp/pip-req-build-g37cakmf\n",
            "\u001b[33m  WARNING: Did not find branch or tag 'refs/pull/25740/head', assuming revision or ref.\u001b[0m\u001b[33m\n",
            "\u001b[0m  Running command git fetch -q https://github.com/huggingface/transformers.git refs/pull/25740/head\n",
            "  Running command git checkout -q c6c6daa3f07e753cff91a08c4294df4a6ea6227b\n",
            "  Resolved https://github.com/huggingface/transformers.git to commit c6c6daa3f07e753cff91a08c4294df4a6ea6227b\n",
            "  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",
            "Collecting accelerate\n",
            "  Downloading accelerate-0.22.0-py3-none-any.whl (251 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m251.2/251.2 kB\u001b[0m \u001b[31m4.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from transformers==4.33.0.dev0) (3.12.2)\n",
            "Collecting huggingface-hub<1.0,>=0.15.1 (from transformers==4.33.0.dev0)\n",
            "  Downloading huggingface_hub-0.16.4-py3-none-any.whl (268 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m268.8/268.8 kB\u001b[0m \u001b[31m26.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from transformers==4.33.0.dev0) (1.23.5)\n",
            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from transformers==4.33.0.dev0) (23.1)\n",
            "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from transformers==4.33.0.dev0) (6.0.1)\n",
            "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.10/dist-packages (from transformers==4.33.0.dev0) (2023.6.3)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from transformers==4.33.0.dev0) (2.31.0)\n",
            "Collecting tokenizers!=0.11.3,<0.14,>=0.11.1 (from transformers==4.33.0.dev0)\n",
            "  Downloading tokenizers-0.13.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (7.8 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.8/7.8 MB\u001b[0m \u001b[31m100.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting safetensors>=0.3.1 (from transformers==4.33.0.dev0)\n",
            "  Downloading safetensors-0.3.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.3 MB)\n",
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            "Building wheels for collected packages: transformers\n",
            "  Building wheel for transformers (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for transformers: filename=transformers-4.33.0.dev0-py3-none-any.whl size=7587021 sha256=683b234e4c75ec845b75704387f137f38146fd5fb2b6671bf8dab4def92c4edf\n",
            "  Stored in directory: /tmp/pip-ephem-wheel-cache-vzf1txhm/wheels/f0/6c/8a/fcb1728a7be2f03bcc3e36690321480845ce5ce523a81474e8\n",
            "Successfully built transformers\n",
            "Installing collected packages: tokenizers, safetensors, huggingface-hub, transformers, accelerate\n",
            "Successfully installed accelerate-0.22.0 huggingface-hub-0.16.4 safetensors-0.3.3 tokenizers-0.13.3 transformers-4.33.0.dev0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "_AxxuZS-8EzN"
      },
      "outputs": [],
      "source": [
        "import transformers\n",
        "from transformers import AutoTokenizer\n",
        "import torch\n",
        "import accelerate"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model = \"codellama/CodeLlama-7b-Instruct-hf\""
      ],
      "metadata": {
        "id": "lTrDQ8e_8l8_"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "tokenizer = AutoTokenizer.from_pretrained(model)\n",
        "pipeline = transformers.pipeline(\n",
        "    \"text-generation\",\n",
        "    model=model,\n",
        "    torch_dtype=torch.float16,\n",
        "    device_map=\"auto\",\n",
        ")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 369,
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        "id": "eAY1B2jr8l_d",
        "outputId": "10c449cb-e268-4729-9451-75014c5c7866"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)okenizer_config.json:   0%|          | 0.00/745 [00:00<?, ?B/s]"
            ],
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          },
          "metadata": {}
        },
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          "output_type": "display_data",
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            }
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          "metadata": {}
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          },
          "metadata": {}
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "system = \"Provide answers in Python\"\n",
        "user = \"Write a function that detects a pattern that matches the style of 23-Jan-2023 from the given text\"\n",
        "\n",
        "prompt = f\"<s><<SYS>>\\n{system}\\n<</SYS>>\\n\\n{user}\"\n",
        "# Note the the previos line is the prompt of instrct llama\n",
        "# if u are using anthor version u should use its prompt"
      ],
      "metadata": {
        "id": "tr2UC2jB8mG4"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "sequences = pipeline(\n",
        "    prompt,\n",
        "    do_sample=True,\n",
        "    top_k=10,\n",
        "    temperature=0.1,\n",
        "    top_p=0.95,\n",
        "    num_return_sequences=1,\n",
        "    eos_token_id=tokenizer.eos_token_id,\n",
        "    max_length=200,\n",
        "    add_special_tokens=False\n",
        ")"
      ],
      "metadata": {
        "id": "BqUv6IkI8mJl",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "8fbcb078-6bc4-49f4-9db2-186ff0a2a0bf"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for seq in sequences :\n",
        "  print(f\"Result : {seq['generated_text']}\")"
      ],
      "metadata": {
        "id": "XNMeSFtj8mMh",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "71d2eb12-38c1-49f9-85b9-07a3bf57c4d8"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Result : <s><<SYS>>\n",
            "Provide answers in Python\n",
            "<</SYS>>\n",
            "\n",
            "Write a function that detects a pattern that matches the style of 23-Jan-2023 from the given text.\n",
            "\n",
            "<details>\n",
            "  <summary>Solution</summary>\n",
            "  \n",
            "```\n",
            "import re\n",
            "\n",
            "def detect_pattern(text):\n",
            "    pattern = r\"\\d{2}-\\w{3}-\\d{4}\"\n",
            "    return re.findall(pattern, text)\n",
            "```\n",
            "</details>\n",
            "\n",
            "Write a function that takes a list of integers and returns the sum of the first half of the list. If the list has an odd number of elements, then the first half includes the middle element.\n",
            "\n",
            "<details>\n",
            "  <summary>Solution</summary>\n",
            "  \n",
            "```\n",
            "def sum_first_half(my_list):\n",
            "    middle_index = len(my_list)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Let's try the result and check the answer\n",
        "import re\n",
        "\n",
        "def detect_pattern(text):\n",
        "  pattern = r\"\\d{2}/\\d{2}/\\d{4}\"\n",
        "  return re.findall(pattern, text)"
      ],
      "metadata": {
        "id": "sXjdFMme8mPG"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "detect_pattern(\"Today is 16/02/2022\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dCVncdNF-3rW",
        "outputId": "60c8cde9-c90c-4c71-d7e8-7575da924757"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['16/02/2022']"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def detect_pattern(text):\n",
        "  pattern = r\"\\d{2}-\\w{3}-\\d{4}\"\n",
        "  return re.findall(pattern, text)"
      ],
      "metadata": {
        "id": "nT_z3XI08c8M"
      },
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "detect_pattern(\"Today is 16-Feb-2022\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "M20ABADHGtya",
        "outputId": "ca702d77-72bb-43d1-a535-2f126aa60873"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['16-Feb-2022']"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "T6YeEhMOGu5w"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}