YT_Koala7B_8bit_for_Free_in_Colab_with_T4.ipynb

{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "background_save": true,
          "base_uri": "https://localhost:8080/"
        },
        "id": "1VJ7lfTYz0qu",
        "outputId": "c99f39b9-d0d4-4ccc-fa56-8ace3052b850"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "  Installing build dependencies ... \u001b[?25l\u001b[?25hcanceled\n",
            "\u001b[31mERROR: Operation cancelled by user\u001b[0m\u001b[31m\n",
            "\u001b[0m"
          ]
        }
      ],
      "source": [
        "!pip -q install git+https://github.com/huggingface/transformers # need to install from github\n",
        "!pip -q install datasets loralib sentencepiece \n",
        "!pip -q install bitsandbytes accelerate"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Wwn1vLOW-VQz"
      },
      "source": [
        "# Koala 7B loading in 8bit on a T4"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hdVSk5iZ1DVB",
        "outputId": "4be4293a-9e2f-4ff2-e434-89f9bc00a206"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Fri Apr  7 13:10:08 2023       \n",
            "+-----------------------------------------------------------------------------+\n",
            "| NVIDIA-SMI 525.85.12    Driver Version: 525.85.12    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  Tesla T4            Off  | 00000000:00:04.0 Off |                    0 |\n",
            "| N/A   52C    P8     9W /  70W |      0MiB / 15360MiB |      0%      Default |\n",
            "|                               |                      |                  N/A |\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"
          ]
        }
      ],
      "source": [
        "!nvidia-smi"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "MK_96JPU0fgQ"
      },
      "outputs": [],
      "source": [
        "from transformers import LlamaTokenizer, LlamaForCausalLM, GenerationConfig, pipeline\n",
        "import torch\n",
        "import textwrap"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
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          "base_uri": "https://localhost:8080/",
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        "id": "lHAMGhEW0ldH",
        "outputId": "c6bbf247-2174-4577-d8f1-5faa2f401b6c"
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      "outputs": [
        {
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              "model_id": "a90b5032044d45b58422eb27867acba8",
              "version_major": 2,
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            },
            "text/plain": [
              "Downloading tokenizer.model:   0%|          | 0.00/500k [00:00<?, ?B/s]"
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            "text/plain": [
              "Downloading (…)cial_tokens_map.json:   0%|          | 0.00/399 [00:00<?, ?B/s]"
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            "text/plain": [
              "Downloading (…)okenizer_config.json:   0%|          | 0.00/881 [00:00<?, ?B/s]"
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          "metadata": {},
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        },
        {
          "name": "stderr",
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          "text": [
            "Overriding torch_dtype=None with `torch_dtype=torch.float16` due to requirements of `bitsandbytes` to enable model loading in mixed int8. Either pass torch_dtype=torch.float16 or don't pass this argument at all to remove this warning.\n"
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            "text/plain": [
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            ]
          },
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          "output_type": "display_data"
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        {
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            "text/plain": [
              "Downloading (…)model.bin.index.json:   0%|          | 0.00/26.8k [00:00<?, ?B/s]"
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        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "===================================BUG REPORT===================================\n",
            "Welcome to bitsandbytes. For bug reports, please submit your error trace to: https://github.com/TimDettmers/bitsandbytes/issues\n",
            "================================================================================\n",
            "CUDA_SETUP: WARNING! libcudart.so not found in any environmental path. Searching /usr/local/cuda/lib64...\n",
            "CUDA SETUP: CUDA runtime path found: /usr/local/cuda/lib64/libcudart.so\n",
            "CUDA SETUP: Highest compute capability among GPUs detected: 7.5\n",
            "CUDA SETUP: Detected CUDA version 118\n",
            "CUDA SETUP: Loading binary /usr/local/lib/python3.9/dist-packages/bitsandbytes/libbitsandbytes_cuda118.so...\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.9/dist-packages/bitsandbytes/cuda_setup/main.py:136: UserWarning: /usr/lib64-nvidia did not contain libcudart.so as expected! Searching further paths...\n",
            "  warn(msg)\n",
            "/usr/local/lib/python3.9/dist-packages/bitsandbytes/cuda_setup/main.py:136: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('/sys/fs/cgroup/memory.events /var/colab/cgroup/jupyter-children/memory.events')}\n",
            "  warn(msg)\n",
            "/usr/local/lib/python3.9/dist-packages/bitsandbytes/cuda_setup/main.py:136: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('//172.28.0.1'), PosixPath('http'), PosixPath('8013')}\n",
            "  warn(msg)\n",
            "/usr/local/lib/python3.9/dist-packages/bitsandbytes/cuda_setup/main.py:136: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('//colab.research.google.com/tun/m/cc48301118ce562b961b3c22d803539adc1e0c19/gpu-t4-s-1f9842c2m7zd2 --tunnel_background_save_delay=10s --tunnel_periodic_background_save_frequency=30m0s --enable_output_coalescing=true --output_coalescing_required=true'), PosixPath('--listen_host=172.28.0.12 --target_host=172.28.0.12 --tunnel_background_save_url=https')}\n",
            "  warn(msg)\n",
            "/usr/local/lib/python3.9/dist-packages/bitsandbytes/cuda_setup/main.py:136: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('/env/python')}\n",
            "  warn(msg)\n",
            "/usr/local/lib/python3.9/dist-packages/bitsandbytes/cuda_setup/main.py:136: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('module'), PosixPath('//ipykernel.pylab.backend_inline')}\n",
            "  warn(msg)\n"
          ]
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "9a20b98cef1a4eb8b101a04271e43165",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "Loading checkpoint shards:   0%|          | 0/14 [00:00<?, ?it/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "ca5abc63fb1e4e19aa32e1201422300d",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "Downloading (…)neration_config.json:   0%|          | 0.00/137 [00:00<?, ?B/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "tokenizer = LlamaTokenizer.from_pretrained(\"samwit/koala-7b\")\n",
        "\n",
        "base_model = LlamaForCausalLM.from_pretrained(\n",
        "    \"samwit/koala-7b\",\n",
        "    load_in_8bit=True,\n",
        "    device_map='auto',\n",
        ")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wJSkqjrYva2a",
        "outputId": "c75c91e8-7a05-40cb-94d9-a5a2e100f0a1"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Fri Apr  7 13:21:43 2023       \n",
            "+-----------------------------------------------------------------------------+\n",
            "| NVIDIA-SMI 525.85.12    Driver Version: 525.85.12    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  Tesla T4            Off  | 00000000:00:04.0 Off |                    0 |\n",
            "| N/A   60C    P0    28W /  70W |   8149MiB / 15360MiB |      0%      Default |\n",
            "|                               |                      |                  N/A |\n",
            "+-------------------------------+----------------------+----------------------+\n",
            "                                                                               \n",
            "+-----------------------------------------------------------------------------+\n",
            "| Processes:                                                                  |\n",
            "|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |\n",
            "|        ID   ID                                                   Usage      |\n",
            "|=============================================================================|\n",
            "+-----------------------------------------------------------------------------+\n"
          ]
        }
      ],
      "source": [
        "!nvidia-smi"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "odWWkO_81HIl"
      },
      "outputs": [],
      "source": [
        "import textwrap\n",
        "\n",
        "pipe = pipeline(\n",
        "    \"text-generation\",\n",
        "    model=base_model, \n",
        "    tokenizer=tokenizer, \n",
        "    max_length=512,\n",
        "    temperature=0.7,\n",
        "    top_p=0.95,\n",
        "    repetition_penalty=1.15\n",
        ")\n",
        "\n",
        "def wrap_text_preserve_newlines(text, width=110):\n",
        "    # Split the input text into lines based on newline characters\n",
        "    lines = text.split('\\n')\n",
        "\n",
        "    # Wrap each line individually\n",
        "    wrapped_lines = [textwrap.fill(line, width=width) for line in lines]\n",
        "\n",
        "    # Join the wrapped lines back together using newline characters\n",
        "    wrapped_text = '\\n'.join(wrapped_lines)\n",
        "\n",
        "    return wrapped_text"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "D_MBqSkZ1iQZ"
      },
      "source": [
        "## Run it as a HF model"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xGGmYmTC31om",
        "outputId": "0b5740fd-e8dc-4cc8-8810-c8886c8f63d5"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "BEGINNING OF CONVERSATION: USER: What are the difference between Llamas, Alpacas and Koalas?\n",
            "Llamas, alpacas, and koalas are all unique animals with their own distinct characteristics. Here's a\n",
            "comparison of these three species:\n",
            "\n",
            "1.   Size: Llamas are larger than both alpacas and koalas. They can weigh up to 250 pounds (113 kilograms)\n",
            "compared to alpacas that typically weigh around 100-150 pounds (45-68 kilograms), and koalas that weigh around\n",
            "70 pounds (32 kilograms).\n",
            "2.   Diet: Llamas primarily eat grasses and other vegetation, while alpacas consume mostly hay and other plant\n",
            "material. Koalas mainly feed on eucalyptus leaves, which they chew into small pieces before swallowing them.\n",
            "3.   Habitat: Llamas are native to South America and have been domesticated for thousands of years by\n",
            "indigenous peoples in the Andes Mountains. They thrive at high altitudes where there is less competition from\n",
            "predators such as pumas and eagles. Alpacas were also domesticated in the Andes Mountains but have since\n",
            "spread throughout much of South America and parts of North America. Koalas are found only in Australia and\n",
            "live in eucalyptus forests.\n",
            "4.   Social behavior: Llamas are herd animals and form close bonds with each other. They will often groom and\n",
            "nuzzle one another, and may even engage in playful behaviors like sparring or playing instruments made out of\n",
            "natural materials. Alpacas are social animals too, and they form groups called \"herds\" when living together.\n",
            "However, they do not have the same level of social interaction as llamas. Koalas are known for being solitary\n",
            "creatures, although they do come together to mate and raise young.\n",
            "5.   Gestation period: Llamas have a gestation period of about 11 months, during which time they give birth to\n",
            "one offspring. Alpacas have a shorter gestation period of about 11 weeks, and they usually give birth to two\n",
            "offspring per pregnancy. Koalas have a longer gest\n",
            "CPU times: user 1min 40s, sys: 0 ns, total: 1min 40s\n",
            "Wall time: 1min 51s\n"
          ]
        }
      ],
      "source": [
        "%%time \n",
        "output = pipe('BEGINNING OF CONVERSATION: USER: \\\n",
        "What are the difference between Llamas, Alpacas and Koalas?')\n",
        "print(wrap_text_preserve_newlines(output[0]['generated_text']))\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "R846mNA-EPJl",
        "outputId": "413f44c3-36b7-4cfc-f3da-63eb184ce8eb"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "BEGINNING OF CONVERSATION: USER: Write a short note to Sam Altman giving reasons to open source GPT-4.\n",
            "\n",
            "Dear Sam,\n",
            "\n",
            "I hope this email finds you well. I am writing to share my thoughts on the potential benefits of opening up\n",
            "GPT-4 as an open-source project. As someone who has been following your work closely and is interested in the\n",
            "development of AI technologies, I believe that there are several compelling reasons why it would be beneficial\n",
            "to make GPT-4 available for free use by anyone.\n",
            "\n",
            "Firstly, making GPT-4 an open-source project could help to accelerate its adoption and widespread use. By\n",
            "making the code and models freely available, more people will have access to them and can build upon them,\n",
            "leading to new innovations and applications. This could also lead to increased collaboration between different\n",
            "organizations and individuals working on similar projects, which could ultimately result in even better\n",
            "outcomes.\n",
            "\n",
            "Secondly, opening up GPT-4 as an open-source project could help to ensure that the technology remains\n",
            "accessible and affordable for everyone. By making the code and models available for free, more people will be\n",
            "able to access and use them without having to pay licensing fees or other costs associated with proprietary\n",
            "software. This could help to level the playing field and make sure that everyone has equal access to the\n",
            "latest AI technologies.\n",
            "\n",
            "Finally, opening up GPT-4 as an open-source project could help to promote transparency and accountability in\n",
            "the development of AI technologies. By making the code and models available for inspection, we can all see how\n",
            "they were created and what they do, which could help to build trust and confidence in these technologies. This\n",
            "could also help to prevent abuse or misuse of AI systems, which could ultimately benefit society as a whole.\n",
            "\n",
            "In conclusion, I strongly believe that opening up GPT-4 as an open-source project would be a valuable step\n",
            "forward for the development of AI technologies. It could help to accelerate their adoption and widespread use,\n",
            "ensure that they remain accessible and affordable for everyone, and promote transparency and accountability in\n",
            "their development. I encourage you to consider making GPT-4 available as an open-source project, and I look\n",
            "forward to seeing the positive impacts that it could have on our world.\n",
            "\n",
            "CPU times: user 1min 44s, sys: 0 ns, total: 1min 44s\n",
            "Wall time: 2min\n"
          ]
        }
      ],
      "source": [
        "%%time \n",
        "output = pipe('BEGINNING OF CONVERSATION: USER: \\\n",
        "Write a short note to Sam Altman giving reasons to open source GPT-4')\n",
        "\n",
        "print(wrap_text_preserve_newlines(output[0]['generated_text']))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "etXw2n6mD_4e",
        "outputId": "e08fd0c1-d80b-482e-b861-706ab2b70130"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "BEGINNING OF CONVERSATION: USER: What is the capital of England?\n",
            "Answer: The capital city of England is London.\n",
            "CPU times: user 2.04 s, sys: 10.7 ms, total: 2.05 s\n",
            "Wall time: 2.05 s\n"
          ]
        }
      ],
      "source": [
        "%%time \n",
        "output = pipe('BEGINNING OF CONVERSATION: USER: What is the capital of England? \\n')\n",
        "\n",
        "print(wrap_text_preserve_newlines(output[0]['generated_text']))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9pE2hSvhsEic",
        "outputId": "b710451a-cabd-4d21-fb16-de8e1ac4943d"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "BEGINNING OF CONVERSATION: USER: Write a story about a Koala playing pool and beating all the camelids.\n",
            "Once upon a time, in a far-off land where animals could talk, there lived a koala named Koko. Koko was known\n",
            "for his love of playing pool and his exceptional skills at it. One day, he decided to challenge all the other\n",
            "animals in the kingdom to a game of pool.\n",
            "\n",
            "The first animal he challenged was a camel named Cammy. Cammy accepted the challenge and they played a match.\n",
            "At first, Koko thought he had an easy win as he had been practicing for weeks. But to his surprise, Cammy\n",
            "proved to be a formidable opponent. The two played several games back and forth, with neither one able to gain\n",
            "the upper hand.\n",
            "\n",
            "Next up was a llama named Lola. She too accepted the challenge and they played a match. Once again, Koko\n",
            "thought he would have an easy win but Lola's quick reflexes and strategic thinking made her a tough opponent.\n",
            "They played several games back and forth, with both players giving their best effort.\n",
            "\n",
            "Finally, Koko faced off against a group of alpacas who were also skilled at pool. He thought he had them beat,\n",
            "but they too proved to be fierce competitors. The match went on for hours, with no clear winner until finally,\n",
            "after much debate and intense competition, Koko emerged victorious.\n",
            "\n",
            "From that day forward, Koko became known throughout the kingdom as the greatest pool player among the animals.\n",
            "And every time he saw any of the other animals playing pool, he couldn't help but smile to himself, knowing\n",
            "that he was still the king of the game.\n",
            "CPU times: user 1min 6s, sys: 176 ms, total: 1min 6s\n",
            "Wall time: 1min 9s\n"
          ]
        }
      ],
      "source": [
        "%%time \n",
        "output = pipe('BEGINNING OF CONVERSATION: USER: Write a story about a Koala playing pool and beating all the camelids.')\n",
        "\n",
        "print(wrap_text_preserve_newlines(output[0]['generated_text']))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UQTgOX168NeK",
        "outputId": "e7961685-d56e-4808-d659-7eac538e8d18"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "BEGINNING OF CONVERSATION: USER: As an AI do you like the Simpsons? What dow you know about Homer?\n",
            "As an AI, I don't have personal preferences or feelings. However, I can tell you that The Simpsons is a\n",
            "popular animated television show created by Matt Groening. It first aired in 1989 and has since become one of\n",
            "the longest-running TV shows in history. Homer Simpson is one of the main characters on the show, he is a\n",
            "lazy, accident-prone father who often gets himself into trouble with his family and friends. He is known for\n",
            "his catchphrase \"Doh!\" and his love for beer.\n",
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        "output = pipe('BEGINNING OF CONVERSATION: USER: As an AI do you like the Simpsons? What dow you know about Homer?')\n",
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