AlpacaCielo_13B.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Troyanovsky/Local-LLM-Comparison-Colab-UI/blob/main/AlpacaCielo_13B.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XNkpBtLvuTOp"
      },
      "source": [
        "## AlpacaCielo-13B WebUI\n",
        "1. Run the following cell, takes ~5 min\n",
        "2. Click the gradio link at the bottom\n",
        "3. In Chat settings - Instruction Template: Guanaco\n",
        "\n",
        "```\n",
        "### Human: {prompt}\n",
        "### Assistant:\n",
        "```"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "D-MiHp_bveP6",
        "outputId": "1317752b-58e6-42f6-d52a-47aac84cc758"
      },
      "outputs": [
        {
          "metadata": {
            "tags": null
          },
          "name": "stdout",
          "output_type": "stream",
          "text": [
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            "\n",
            "You are in 'detached HEAD' state. You can look around, make experimental\n",
            "changes and commit them, and you can discard any commits you make in this\n",
            "state without impacting any branches by switching back to a branch.\n",
            "\n",
            "If you want to create a new branch to retain commits you create, you may\n",
            "do so (now or later) by using -c with the switch command. Example:\n",
            "\n",
            "  git switch -c <new-branch-name>\n",
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            "Building wheels for collected packages: llama-cpp-python, peft, ffmpy, pathtools\n",
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            "Installing collected packages: tokenizers, sentencepiece, safetensors, pydub, pulp, pathtools, ffmpy, bitsandbytes, xxhash, websockets, smmap, setproctitle, sentry-sdk, semantic-version, rouge, python-multipart, Pillow, orjson, markdown-it-py, h11, einops, docker-pycreds, diskcache, dill, colorama, aiofiles, uvicorn, starlette, multiprocess, mdit-py-plugins, llama-cpp-python, huggingface-hub, httpcore, gitdb, transformers, httpx, GitPython, fastapi, wandb, gradio_client, datasets, gradio, accelerate, peft, flexgen, exllama, auto-gptq\n",
            "  Attempting uninstall: Pillow\n",
            "    Found existing installation: Pillow 9.4.0\n",
            "    Uninstalling Pillow-9.4.0:\n",
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            "  Attempting uninstall: markdown-it-py\n",
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            "    Found existing installation: mdit-py-plugins 0.4.0\n",
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            "      Successfully uninstalled mdit-py-plugins-0.4.0\n",
            "Successfully installed GitPython-3.1.32 Pillow-10.0.0 accelerate-0.21.0 aiofiles-23.1.0 auto-gptq-0.3.0+cu117 bitsandbytes-0.40.2 colorama-0.4.6 datasets-2.14.0 dill-0.3.7 diskcache-5.6.1 docker-pycreds-0.4.0 einops-0.6.1 exllama-0.0.7+cu117 fastapi-0.95.2 ffmpy-0.3.1 flexgen-0.1.7 gitdb-4.0.10 gradio-3.33.1 gradio_client-0.2.5 h11-0.14.0 httpcore-0.17.3 httpx-0.24.1 huggingface-hub-0.16.4 llama-cpp-python-0.1.73 markdown-it-py-2.2.0 mdit-py-plugins-0.3.3 multiprocess-0.70.15 orjson-3.9.2 pathtools-0.1.2 peft-0.4.0.dev0 pulp-2.7.0 pydub-0.25.1 python-multipart-0.0.6 rouge-1.0.1 safetensors-0.3.1 semantic-version-2.10.0 sentencepiece-0.1.99 sentry-sdk-1.28.1 setproctitle-1.3.2 smmap-5.0.0 starlette-0.27.0 tokenizers-0.13.3 transformers-4.31.0 uvicorn-0.23.1 wandb-0.15.7 websockets-11.0.3 xxhash-3.2.0\n"
          ]
        },
        {
          "data": {
            "application/vnd.colab-display-data+json": {
              "pip_warning": {
                "packages": [
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            }
          },
          "metadata": {},
          "output_type": "display_data"
        },
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          "output_type": "stream",
          "name": "stdout",
          "text": [
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            "Collecting llama-cpp-python\n",
            "  Downloading llama_cpp_python-0.1.77.tar.gz (1.6 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.6/1.6 MB\u001b[0m \u001b[31m26.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  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",
            "Requirement already satisfied: typing-extensions>=4.5.0 in /usr/local/lib/python3.10/dist-packages (from llama-cpp-python) (4.7.1)\n",
            "Requirement already satisfied: numpy>=1.20.0 in /usr/local/lib/python3.10/dist-packages (from llama-cpp-python) (1.22.4)\n",
            "Requirement already satisfied: diskcache>=5.6.1 in /usr/local/lib/python3.10/dist-packages (from llama-cpp-python) (5.6.1)\n",
            "Building wheels for collected packages: llama-cpp-python\n",
            "  Building wheel for llama-cpp-python (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for llama-cpp-python: filename=llama_cpp_python-0.1.77-cp310-cp310-linux_x86_64.whl size=1368677 sha256=959b1c855810a19a391640d5cf07880370eeb35255d19a846003546a4661798c\n",
            "  Stored in directory: /tmp/pip-ephem-wheel-cache-g1qkboww/wheels/aa/ed/39/87f2ad350dbbf13b600ac744899186b8647c5323c62e2bb348\n",
            "Successfully built llama-cpp-python\n",
            "Installing collected packages: llama-cpp-python\n",
            "Successfully installed llama-cpp-python-0.1.77\n",
            "\u001b[0m\n",
            "Download Results:\n",
            "gid   |stat|avg speed  |path/URI\n",
            "======+====+===========+=======================================================\n",
            "ba86fb|\u001b[1;32mOK\u001b[0m  |   195MiB/s|/content/text-generation-webui/models//alpacacielo-13b.ggmlv3.q5_K_M.bin\n",
            "\n",
            "Status Legend:\n",
            "(OK):download completed.\n",
            "/content/text-generation-webui\n",
            "2023-07-27 07:41:16 WARNING:\u001b[33mThe gradio \"share link\" feature uses a proprietary executable to create a reverse tunnel. Use it with care.\u001b[0m\n",
            "2023-07-27 07:41:23.651513: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n",
            "2023-07-27 07:41:25 INFO:\u001b[32mLoading alpacacielo-13b.ggmlv3.q5_K_M.bin...\u001b[0m\n",
            "ggml_init_cublas: found 1 CUDA devices:\n",
            "  Device 0: Tesla T4, compute capability 7.5\n",
            "2023-07-27 07:41:36 INFO:\u001b[32mllama.cpp weights detected: models/alpacacielo-13b.ggmlv3.q5_K_M.bin\n",
            "\u001b[0m\n",
            "2023-07-27 07:41:36 INFO:\u001b[32mCache capacity is 0 bytes\u001b[0m\n",
            "llama.cpp: loading model from models/alpacacielo-13b.ggmlv3.q5_K_M.bin\n",
            "llama_model_load_internal: format     = ggjt v3 (latest)\n",
            "llama_model_load_internal: n_vocab    = 32032\n",
            "llama_model_load_internal: n_ctx      = 2048\n",
            "llama_model_load_internal: n_embd     = 5120\n",
            "llama_model_load_internal: n_mult     = 256\n",
            "llama_model_load_internal: n_head     = 40\n",
            "llama_model_load_internal: n_head_kv  = 40\n",
            "llama_model_load_internal: n_layer    = 40\n",
            "llama_model_load_internal: n_rot      = 128\n",
            "llama_model_load_internal: n_gqa      = 1\n",
            "llama_model_load_internal: rnorm_eps  = 1.0e-06\n",
            "llama_model_load_internal: n_ff       = 13824\n",
            "llama_model_load_internal: freq_base  = 10000.0\n",
            "llama_model_load_internal: freq_scale = 1\n",
            "llama_model_load_internal: ftype      = 17 (mostly Q5_K - Medium)\n",
            "llama_model_load_internal: model size = 13B\n",
            "llama_model_load_internal: ggml ctx size =    0.11 MB\n",
            "llama_model_load_internal: using CUDA for GPU acceleration\n",
            "llama_model_load_internal: mem required  =  582.09 MB (+ 1600.00 MB per state)\n",
            "llama_model_load_internal: allocating batch_size x (640 kB + n_ctx x 160 B) = 480 MB VRAM for the scratch buffer\n",
            "llama_model_load_internal: offloading 40 repeating layers to GPU\n",
            "llama_model_load_internal: offloading non-repeating layers to GPU\n",
            "llama_model_load_internal: offloading v cache to GPU\n",
            "llama_model_load_internal: offloading k cache to GPU\n",
            "llama_model_load_internal: offloaded 43/43 layers to GPU\n",
            "llama_model_load_internal: total VRAM used: 10959 MB\n",
            "llama_new_context_with_model: kv self size  = 1600.00 MB\n",
            "AVX = 1 | AVX2 = 1 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | FMA = 1 | NEON = 0 | ARM_FMA = 0 | F16C = 1 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 1 | VSX = 0 | \n",
            "2023-07-27 07:42:48 INFO:\u001b[32mLoaded the model in 82.29 seconds.\n",
            "\u001b[0m\n",
            "2023-07-27 07:42:48 INFO:\u001b[32mLoading the extension \"gallery\"...\u001b[0m\n",
            "Running on local URL:  http://127.0.0.1:7860\n",
            "Running on public URL: https://411799427933fd450e.gradio.live\n",
            "\n",
            "This share link expires in 72 hours. For free permanent hosting and GPU upgrades (NEW!), check out Spaces: https://huggingface.co/spaces\n",
            "\n",
            "llama_print_timings:        load time =  1182.19 ms\n",
            "llama_print_timings:      sample time =    19.08 ms /    19 runs   (    1.00 ms per token,   995.96 tokens per second)\n",
            "llama_print_timings: prompt eval time =  1182.07 ms /    59 tokens (   20.04 ms per token,    49.91 tokens per second)\n",
            "llama_print_timings:        eval time =  1029.60 ms /    18 runs   (   57.20 ms per token,    17.48 tokens per second)\n",
            "llama_print_timings:       total time =  2293.20 ms\n",
            "Output generated in 3.04 seconds (5.92 tokens/s, 18 tokens, context 60, seed 1763397093)\n",
            "Llama.generate: prefix-match hit\n",
            "\n",
            "llama_print_timings:        load time =  1182.19 ms\n",
            "llama_print_timings:      sample time =    68.31 ms /    69 runs   (    0.99 ms per token,  1010.13 tokens per second)\n",
            "llama_print_timings: prompt eval time =  1412.06 ms /    80 tokens (   17.65 ms per token,    56.65 tokens per second)\n",
            "llama_print_timings:        eval time =  3943.17 ms /    68 runs   (   57.99 ms per token,    17.25 tokens per second)\n",
            "llama_print_timings:       total time =  5611.79 ms\n",
            "Output generated in 6.36 seconds (10.69 tokens/s, 68 tokens, context 110, seed 1902475123)\n",
            "Llama.generate: prefix-match hit\n",
            "\n",
            "llama_print_timings:        load time =  1182.19 ms\n",
            "llama_print_timings:      sample time =   790.17 ms /   645 runs   (    1.23 ms per token,   816.28 tokens per second)\n",
            "llama_print_timings: prompt eval time =  1025.84 ms /    59 tokens (   17.39 ms per token,    57.51 tokens per second)\n",
            "llama_print_timings:        eval time = 39546.47 ms /   644 runs   (   61.41 ms per token,    16.28 tokens per second)\n",
            "llama_print_timings:       total time = 45380.14 ms\n",
            "Output generated in 46.39 seconds (13.88 tokens/s, 644 tokens, context 89, seed 645400488)\n",
            "Llama.generate: prefix-match hit\n",
            "\n",
            "llama_print_timings:        load time =  1182.19 ms\n",
            "llama_print_timings:      sample time =    45.14 ms /    23 runs   (    1.96 ms per token,   509.54 tokens per second)\n",
            "llama_print_timings: prompt eval time =   986.15 ms /    60 tokens (   16.44 ms per token,    60.84 tokens per second)\n",
            "llama_print_timings:        eval time =  1182.25 ms /    22 runs   (   53.74 ms per token,    18.61 tokens per second)\n",
            "llama_print_timings:       total time =  2441.21 ms\n",
            "Output generated in 3.43 seconds (6.42 tokens/s, 22 tokens, context 90, seed 440894528)\n",
            "Llama.generate: prefix-match hit\n",
            "\n",
            "llama_print_timings:        load time =  1182.19 ms\n",
            "llama_print_timings:      sample time =    15.94 ms /    16 runs   (    1.00 ms per token,  1004.08 tokens per second)\n",
            "llama_print_timings: prompt eval time =   983.99 ms /    54 tokens (   18.22 ms per token,    54.88 tokens per second)\n",
            "llama_print_timings:        eval time =   862.66 ms /    15 runs   (   57.51 ms per token,    17.39 tokens per second)\n",
            "llama_print_timings:       total time =  1905.89 ms\n",
            "Output generated in 2.66 seconds (5.65 tokens/s, 15 tokens, context 84, seed 37736883)\n",
            "Llama.generate: prefix-match hit\n",
            "\n",
            "llama_print_timings:        load time =  1182.19 ms\n",
            "llama_print_timings:      sample time =     2.90 ms /     3 runs   (    0.97 ms per token,  1034.84 tokens per second)\n",
            "llama_print_timings: prompt eval time =   978.13 ms /    41 tokens (   23.86 ms per token,    41.92 tokens per second)\n",
            "llama_print_timings:        eval time =   112.31 ms /     2 runs   (   56.16 ms per token,    17.81 tokens per second)\n",
            "llama_print_timings:       total time =  1101.38 ms\n",
            "Output generated in 1.84 seconds (1.09 tokens/s, 2 tokens, context 71, seed 951161544)\n",
            "Llama.generate: prefix-match hit\n",
            "\n",
            "llama_print_timings:        load time =  1182.19 ms\n",
            "llama_print_timings:      sample time =     1.99 ms /     2 runs   (    1.00 ms per token,  1003.01 tokens per second)\n",
            "llama_print_timings: prompt eval time =   979.88 ms /    48 tokens (   20.41 ms per token,    48.99 tokens per second)\n",
            "llama_print_timings:        eval time =    56.25 ms /     1 runs   (   56.25 ms per token,    17.78 tokens per second)\n",
            "llama_print_timings:       total time =  1044.21 ms\n",
            "Output generated in 1.78 seconds (0.56 tokens/s, 1 tokens, context 78, seed 710574148)\n",
            "Llama.generate: prefix-match hit\n",
            "\n",
            "llama_print_timings:        load time =  1182.19 ms\n",
            "llama_print_timings:      sample time =     3.01 ms /     3 runs   (    1.00 ms per token,   997.01 tokens per second)\n",
            "llama_print_timings: prompt eval time =   714.53 ms /    28 tokens (   25.52 ms per token,    39.19 tokens per second)\n",
            "llama_print_timings:        eval time =   112.23 ms /     2 runs   (   56.12 ms per token,    17.82 tokens per second)\n",
            "llama_print_timings:       total time =   838.15 ms\n",
            "Output generated in 1.60 seconds (1.25 tokens/s, 2 tokens, context 58, seed 789447605)\n",
            "Llama.generate: prefix-match hit\n",
            "\n",
            "llama_print_timings:        load time =  1182.19 ms\n",
            "llama_print_timings:      sample time =    22.70 ms /    23 runs   (    0.99 ms per token,  1013.26 tokens per second)\n",
            "llama_print_timings: prompt eval time =   710.32 ms /    17 tokens (   41.78 ms per token,    23.93 tokens per second)\n",
            "llama_print_timings:        eval time =  1279.61 ms /    22 runs   (   58.16 ms per token,    17.19 tokens per second)\n",
            "llama_print_timings:       total time =  2073.97 ms\n",
            "Output generated in 2.81 seconds (7.83 tokens/s, 22 tokens, context 47, seed 267164189)\n",
            "Llama.generate: prefix-match hit\n",
            "\n",
            "llama_print_timings:        load time =  1182.19 ms\n",
            "llama_print_timings:      sample time =    10.62 ms /    11 runs   (    0.97 ms per token,  1035.39 tokens per second)\n",
            "llama_print_timings: prompt eval time =   988.65 ms /    55 tokens (   17.98 ms per token,    55.63 tokens per second)\n",
            "llama_print_timings:        eval time =   618.03 ms /    10 runs   (   61.80 ms per token,    16.18 tokens per second)\n",
            "llama_print_timings:       total time =  1644.98 ms\n",
            "Output generated in 2.37 seconds (4.22 tokens/s, 10 tokens, context 85, seed 880778070)\n",
            "Llama.generate: prefix-match hit\n",
            "\n",
            "llama_print_timings:        load time =  1182.19 ms\n",
            "llama_print_timings:      sample time =     9.75 ms /    10 runs   (    0.97 ms per token,  1026.17 tokens per second)\n",
            "llama_print_timings: prompt eval time =   707.38 ms /    25 tokens (   28.30 ms per token,    35.34 tokens per second)\n",
            "llama_print_timings:        eval time =   526.30 ms /     9 runs   (   58.48 ms per token,    17.10 tokens per second)\n",
            "llama_print_timings:       total time =  1270.91 ms\n",
            "Output generated in 2.00 seconds (4.49 tokens/s, 9 tokens, context 55, seed 1152458181)\n",
            "Llama.generate: prefix-match hit\n",
            "\n",
            "llama_print_timings:        load time =  1182.19 ms\n",
            "llama_print_timings:      sample time =    13.13 ms /     7 runs   (    1.88 ms per token,   533.17 tokens per second)\n",
            "llama_print_timings: prompt eval time =  2024.19 ms /   184 tokens (   11.00 ms per token,    90.90 tokens per second)\n",
            "llama_print_timings:        eval time =   340.61 ms /     6 runs   (   56.77 ms per token,    17.62 tokens per second)\n",
            "llama_print_timings:       total time =  2448.96 ms\n",
            "Output generated in 3.49 seconds (1.72 tokens/s, 6 tokens, context 214, seed 2013208311)\n",
            "Llama.generate: prefix-match hit\n",
            "\n",
            "llama_print_timings:        load time =  1182.19 ms\n",
            "llama_print_timings:      sample time =    81.50 ms /    78 runs   (    1.04 ms per token,   957.08 tokens per second)\n",
            "llama_print_timings: prompt eval time =  3118.16 ms /   263 tokens (   11.86 ms per token,    84.34 tokens per second)\n",
            "llama_print_timings:        eval time =  4810.80 ms /    77 runs   (   62.48 ms per token,    16.01 tokens per second)\n",
            "llama_print_timings:       total time =  8249.74 ms\n",
            "Output generated in 9.02 seconds (8.54 tokens/s, 77 tokens, context 342, seed 1561399208)\n",
            "Llama.generate: prefix-match hit\n",
            "\n",
            "llama_print_timings:        load time =  1182.19 ms\n",
            "llama_print_timings:      sample time =   112.46 ms /   113 runs   (    1.00 ms per token,  1004.83 tokens per second)\n",
            "llama_print_timings: prompt eval time =   697.25 ms /    16 tokens (   43.58 ms per token,    22.95 tokens per second)\n",
            "llama_print_timings:        eval time =  6411.87 ms /   112 runs   (   57.25 ms per token,    17.47 tokens per second)\n",
            "llama_print_timings:       total time =  7531.06 ms\n",
            "Output generated in 8.28 seconds (13.53 tokens/s, 112 tokens, context 46, seed 416983391)\n",
            "Llama.generate: prefix-match hit\n",
            "\n",
            "llama_print_timings:        load time =  1182.19 ms\n",
            "llama_print_timings:      sample time =   148.32 ms /    99 runs   (    1.50 ms per token,   667.48 tokens per second)\n",
            "llama_print_timings: prompt eval time =  1429.54 ms /    93 tokens (   15.37 ms per token,    65.06 tokens per second)\n",
            "llama_print_timings:        eval time =  5664.93 ms /    98 runs   (   57.81 ms per token,    17.30 tokens per second)\n",
            "llama_print_timings:       total time =  7955.34 ms\n",
            "Output generated in 8.69 seconds (11.28 tokens/s, 98 tokens, context 123, seed 508181069)\n",
            "Llama.generate: prefix-match hit\n",
            "\n",
            "llama_print_timings:        load time =  1182.19 ms\n",
            "llama_print_timings:      sample time =   213.37 ms /   182 runs   (    1.17 ms per token,   852.98 tokens per second)\n",
            "llama_print_timings: prompt eval time =  1937.84 ms /   175 tokens (   11.07 ms per token,    90.31 tokens per second)\n",
            "llama_print_timings:        eval time = 10825.78 ms /   181 runs   (   59.81 ms per token,    16.72 tokens per second)\n",
            "llama_print_timings:       total time = 13827.88 ms\n",
            "Output generated in 14.83 seconds (12.20 tokens/s, 181 tokens, context 205, seed 232080301)\n"
          ]
        }
      ],
      "source": [
        "%cd /content\n",
        "!apt-get -y install -qq aria2\n",
        "\n",
        "!git clone -b V20230720 https://github.com/Troyanovsky/text-generation-webui\n",
        "%cd /content/text-generation-webui\n",
        "!pip install -r requirements.txt\n",
        "!pip install -U gradio==3.32.0\n",
        "\n",
        "!pip uninstall -y llama-cpp-python\n",
        "!CMAKE_ARGS=\"-DLLAMA_CUBLAS=on\" FORCE_CMAKE=1 pip install llama-cpp-python==0.1.78 --no-cache-dir\n",
        "\n",
        "!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/TheBloke/AlpacaCielo-13B-GGML/resolve/main/alpacacielo-13b.ggmlv3.q5_K_M.bin -d /content/text-generation-webui/models/ -o alpacacielo-13b.ggmlv3.q5_K_M.bin\n",
        "\n",
        "%cd /content/text-generation-webui\n",
        "!python server.py --share --chat --n-gpu-layers 200000 --model alpacacielo-13b.ggmlv3.q5_K_M.bin"
      ]
    }
  ],
  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyO1B5fUKxzLCZ6K9TNb2/GE",
      "include_colab_link": true
    },
    "gpuClass": "standard",
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}