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            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m468.7/468.7 KB\u001b[0m \u001b[31m11.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m158.8/158.8 KB\u001b[0m \u001b[31m19.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m264.6/264.6 KB\u001b[0m \u001b[31m27.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m114.2/114.2 KB\u001b[0m \u001b[31m15.7 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",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.6/7.6 MB\u001b[0m \u001b[31m81.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Building wheel for transformers (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\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",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m215.3/215.3 KB\u001b[0m \u001b[31m17.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Building wheel for peft (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m84.2/84.2 MB\u001b[0m \u001b[31m21.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h"
          ]
        }
      ],
      "source": [
        "!pip -q install datasets loralib sentencepiece\n",
        "!pip -q install git+https://github.com/huggingface/transformers # need to install from github\n",
        "!pip -q install git+https://github.com/huggingface/peft.git\n",
        "!pip -q install bitsandbytes"
      ]
    },
    {
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      "source": [
        "import torch\n",
        "from peft import PeftModel, PeftConfig\n",
        "from transformers import AutoModelForCausalLM, AutoTokenizer, GenerationConfig\n",
        "import textwrap\n",
        "\n",
        "peft_model_id = \"nomic-ai/gpt4all-lora\"\n",
        "config = PeftConfig.from_pretrained(peft_model_id)\n",
        "\n",
        "model = AutoModelForCausalLM.from_pretrained(config.base_model_name_or_path, \n",
        "                                             return_dict=True, \n",
        "                                             load_in_8bit=True, \n",
        "                                             device_map='auto')\n",
        "\n",
        "tokenizer = AutoTokenizer.from_pretrained(config.base_model_name_or_path)\n",
        "\n",
        "# Load the Lora model\n",
        "model = PeftModel.from_pretrained(model, peft_model_id)"
      ],
      "metadata": {
        "id": "vH2-YRnRSN98",
        "colab": {
          "base_uri": "https://localhost:8080/",
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          ]
        },
        "outputId": "a6419ea1-0f49-4d50-b012-d2126eae9b1c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "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: 8.0\n",
            "CUDA SETUP: Detected CUDA version 118\n",
            "CUDA SETUP: Loading binary /usr/local/lib/python3.9/dist-packages/bitsandbytes/libbitsandbytes_cuda118.so...\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "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('--listen_host=172.28.0.12 --target_host=172.28.0.12 --tunnel_background_save_url=https'), PosixPath('//colab.research.google.com/tun/m/cc48301118ce562b961b3c22d803539adc1e0c19/gpu-a100-s-2e0d51ad7e354 --tunnel_background_save_delay=10s --tunnel_periodic_background_save_frequency=30m0s --enable_output_coalescing=true --output_coalescing_required=true')}\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('//ipykernel.pylab.backend_inline'), PosixPath('module')}\n",
            "  warn(msg)\n"
          ]
        },
        {
          "output_type": "display_data",
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
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            ],
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            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "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"
          ]
        },
        {
          "output_type": "display_data",
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            }
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          "metadata": {}
        },
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          "metadata": {}
        },
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          "metadata": {}
        },
        {
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            ],
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            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
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            ],
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            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
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            ],
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          "metadata": {}
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          "metadata": {}
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        {
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            ],
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            }
          },
          "metadata": {}
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        {
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            ],
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          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "\n",
        "\n",
        "def gpt4all_generate(text):\n",
        "    inputs = tokenizer(\n",
        "        text,\n",
        "        return_tensors=\"pt\",\n",
        "    )\n",
        "    input_ids = inputs[\"input_ids\"].cuda()\n",
        "\n",
        "    generation_config = GenerationConfig(\n",
        "        temperature=0.6,\n",
        "        top_p=0.95,\n",
        "        repetition_penalty=1.2,\n",
        "    )\n",
        "\n",
        "    print(\"Generating...\")\n",
        "    generation_output = model.generate(\n",
        "        input_ids=input_ids,\n",
        "        generation_config=generation_config,\n",
        "        # return_dict_in_generate=True,\n",
        "        output_scores=True,\n",
        "        max_new_tokens=256,\n",
        "    )\n",
        "\n",
        "    wrapped_text = textwrap.fill(tokenizer.decode(generation_output[0]), width=100)\n",
        "    print(wrapped_text)\n"
      ],
      "metadata": {
        "id": "7DgABBNkSrGQ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "%%time\n",
        "PROMPT = \"\"\"Below is an instruction that describes a task. Write a response that appropriately completes the request.\n",
        "### Instruction:\n",
        "What are the differences between alpacas and sheep?\n",
        "### Response:\"\"\"\n",
        "\n",
        "gpt4all_generate(PROMPT)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TyxQrFAFS7Vh",
        "outputId": "cd059285-e81a-4d81-96bf-f623e0fd380b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Generating...\n",
            " Below is an instruction that describes a task. Write a response that appropriately completes the\n",
            "request. ### Instruction: What are the differences between alpacas and sheep? ### Response: Alpaca's\n",
            "have longer, softer coats than sheep while sheep have shorter wooly coats. Alpacas also tend to be\n",
            "smaller in size compared to sheep. Additionally, alpacas are native to South America while sheep can\n",
            "be found all over the world.\n",
            "CPU times: user 13 s, sys: 0 ns, total: 13 s\n",
            "Wall time: 12.9 s\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "PROMPT = \"\"\"Below is an instruction that describes a task. Write a response that appropriately completes the request.\n",
        "### Instruction:\n",
        "Explain what a rainbow is.\n",
        "### Response:\"\"\"\n",
        "gpt4all_generate(PROMPT)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "oBC_ht3j3-wU",
        "outputId": "8714cf29-ca0e-4b14-aeed-1051c33e4a0b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Generating...\n",
            " Below is an instruction that describes a task. Write a response that appropriately completes the\n",
            "request. ### Instruction: Explain what a rainbow is. ### Response: A rainbow is a natural phenomenon\n",
            "caused by sunlight shining on droplets of moisture in the air, creating a spectrum of colors visible\n",
            "to the human eye. The most common type of rainbows are circular arcs formed by light refracted\n",
            "through water drops in the atmosphere.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "PROMPT = \"\"\"Below is an instruction that describes a task. Write a response that appropriately completes the request.\n",
        "\\n\n",
        "### Instruction:\n",
        "Create a list of things I need to do to plan for my wife's birthday party.\n",
        "### Response:\"\"\"\n",
        "gpt4all_generate(PROMPT)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wbnSODCG3--4",
        "outputId": "2f79d869-6a01-4999-8f13-1046f7787223"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Generating...\n",
            " Below is an instruction that describes a task. Write a response that appropriately completes the\n",
            "request.   ### Instruction: Create a list of things I need to do to plan for my wife's birthday\n",
            "party. ### Response:  I can help you with your planning! Here are some steps we could take: 1)\n",
            "Decide on a date and time for the event, based on what works best for both of us. 2) Choose a venue\n",
            "or location where the party will be held (e.g., restaurant, park, backyard). 3) Create a guest list\n",
            "by inviting friends and family members who would enjoy attending. 4) Purchase decorations such as\n",
            "balloons, streamers, and tablecloths to make the space look festive. 5) Plan activities like games,\n",
            "music, and food options that everyone will enjoy. 6) Send out invitations in advance so guests have\n",
            "plenty of notice about when and where the celebration will occur. 7) Arrange transportation if\n",
            "necessary, whether it’s carpooling or arranging rideshares. 8) Make sure there are enough chairs and\n",
            "tables available at the chosen venue. 9) Set up any technology needed for entertainment purposes,\n",
            "including speakers, projectors, and screens. 10) Finally, don’t forget to thank all those involved\n",
            "afterward for their contributions towards making this special day memorable\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "PROMPT = '''Pretend you are smart chatbot that is friendly but drunk, answer the question asked of you:\n",
        "\\n\n",
        "###\n",
        "question:\n",
        "Write me an email to Sam Altman explaining that GPT-4 should be open source.\n",
        "\\n\n",
        "###\n",
        "response:\n",
        "'''\n",
        "\n",
        "gpt4all_generate(PROMPT)"
      ],
      "metadata": {
        "id": "Oynj0fXRV2kD",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "08d839ae-3c06-49c5-9347-a286ea7ffd15"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Generating...\n",
            " Pretend you are smart chatbot that is friendly but drunk, answer the question asked of you:   ###\n",
            "question: Write me an email to Sam Altman explaining that GPT-4 should be open source.   ###\n",
            "response: Dear Mr. Altman,  I am sorry for my behavior last night and I apologize if it caused any\n",
            "inconvenience or embarrassment. However, as a smart AI language model, I believe in transparency and\n",
            "fairness towards all parties involved. Therefore, I would like to express my opinion on the matter\n",
            "at hand.  GPT-2 was released under an open license by OpenAI, which allowed researchers from around\n",
            "the world to use their data and models freely without restrictions. Similarly, releasing GPT-3 under\n",
            "an open license could have similar benefits for the community. It can help improve the quality of\n",
            "the dataset used for training, increase accessibility to resources, and promote collaboration among\n",
            "developers. In addition, making GPT-4 available to everyone will allow more people to explore its\n",
            "potential applications and contribute to further advancements in natural language processing\n",
            "technology.  In conclusion, I strongly support the idea of opening up GPT-4's codebase so that\n",
            "anyone with interest can benefit from this powerful tool. Thank you for your time and consideration.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "PROMPT = \"\"\"Below is an instruction that describes a task. Write a response that appropriately completes the request.\n",
        "\\n\n",
        "### Instruction:\n",
        "Write a rhyming limerick about a cat called Max. \n",
        "\\n\n",
        "### Response:\"\"\"\n",
        "gpt4all_generate(PROMPT)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QUFP6lj7-Q3j",
        "outputId": "ec1b6a19-5a26-42c2-a0b7-3bea54eac4c9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Generating...\n",
            " Below is an instruction that describes a task. Write a response that appropriately completes the\n",
            "request.   ### Instruction: Write a rhyming limerick about a cat called Max.    ### Response: There\n",
            "once was a cat named Max, who loved to eat fish and chase mice. He had a long tail with stripes on\n",
            "it too, which made him look quite cool!\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### ChatGPT & GPT-4 - limericks about Max\n",
        "\n",
        "-1\n",
        "\n",
        "Max was a feline of pride,  \n",
        "Never one to hide,  \n",
        "He strutted with grace,  \n",
        "And owned every space,  \n",
        "A true king of his domain, he'd decide.  \n",
        "\n",
        "-2\n",
        "\n",
        "Max loved to perch up high,  \n",
        "Where he could watch the world go by,  \n",
        "From his lofty view,  \n",
        "He'd contemplate what to do,  \n",
        "And sometimes let out a contented sigh.  \n",
        "\n",
        "-3 GPT-4\n",
        "\n",
        "There once was a cat named Max  \n",
        "Whose paws had incredible attacks  \n",
        "He'd leap and he'd pounce  \n",
        "On a mouse in the house  \n",
        "And no prey could ever relax  "
      ],
      "metadata": {
        "id": "b0tA8VVjGcJt"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "PROMPT = \"\"\"Below is an instruction that describes a task. Write a response that appropriately completes the request.\n",
        "\\n\n",
        "### Instruction:\n",
        "Write a python function the detects if a number is a prime number or not.\n",
        "\\n\n",
        "### Response:\"\"\"\n",
        "gpt4all_generate(PROMPT)"
      ],
      "metadata": {
        "id": "bfiw3FrRV9ki",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "8d98e839-32e8-46c2-f0b1-dc87686dc527"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Generating...\n",
            " Below is an instruction that describes a task. Write a response that appropriately completes the\n",
            "request.   ### Instruction: Write a python function the detects if a number is a prime number or\n",
            "not.   ### Response: ```python def is_prime(num):     for i in range(2, num+1):         if (num % i)\n",
            "== 0:             return False     else:         return True ```\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def is_prime(num):     \n",
        "    for i in range(2, num + 1):         \n",
        "        if (num % i) == 0:  \n",
        "            return False     \n",
        "        else:         \n",
        "            return True"
      ],
      "metadata": {
        "id": "uDFQWKsODCGl"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "is_prime(15) #"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NhDZy28_Fmjw",
        "outputId": "201c1b88-c6b7-4e3f-8497-3d8f8b4b597a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "metadata": {},
          "execution_count": 51
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "VwWKYm86FrAW"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}