12_Fine_tuning_Microsoft_Phi_1_5b_on_custom_dataset(dialogstudio).ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/ashishpatel26/LLM-Finetuning/blob/main/12_Fine_tuning_Microsoft_Phi_1_5b_on_custom_dataset(dialogstudio).ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SwcwXRajHelL",
        "outputId": "df5a4f77-5b26-42e9-b04d-7d238c321c41"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Thu Sep 21 11:23:52 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  Tesla T4            Off  | 00000000:00:04.0 Off |                    0 |\n",
            "| N/A   60C    P8    11W /  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",
      "source": [
        "!pip install accelerate transformers einops datasets peft bitsandbytes trl"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wH8jsePrSGTH",
        "outputId": "53bf1128-bbbb-4319-c7bb-21820389d3f6"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
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          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "id": "rpf1Z0k4RJM6"
      },
      "outputs": [],
      "source": [
        "# !pip install -Uqqq pip --progress-bar off\n",
        "# !pip install -qqq torch==2.0.1 --progress-bar off\n",
        "# !pip install -qqq transformers==4.32.1 --progress-bar off\n",
        "# !pip install -qqq datasets==2.14.4 --progress-bar off\n",
        "# !pip install -qqq peft==0.5.0 --progress-bar off\n",
        "# !pip install -qqq bitsandbytes==0.41.1 --progress-bar off\n",
        "# !pip install -qqq trl==0.7.1 --progress-bar off"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "id": "P1PG0WSvRqVq"
      },
      "outputs": [],
      "source": [
        "import json\n",
        "import re\n",
        "from pprint import pprint\n",
        "import os\n",
        "\n",
        "import pandas as pd\n",
        "import torch\n",
        "from datasets import Dataset, load_dataset\n",
        "from huggingface_hub import notebook_login\n",
        "from peft import LoraConfig, PeftModel, get_peft_model\n",
        "from transformers import (\n",
        "    AutoModelForCausalLM,\n",
        "    AutoTokenizer,\n",
        "    BitsAndBytesConfig,\n",
        "    TrainingArguments,\n",
        "    DataCollatorForLanguageModeling,\n",
        "    BitsAndBytesConfig\n",
        ")\n",
        "from trl import SFTTrainer\n",
        "\n",
        "DEVICE = \"cuda:0\" if torch.cuda.is_available() else \"cpu\"\n",
        "MODEL_NAME = \"microsoft/phi-1_5\""
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4ixsX2Y4doEf"
      },
      "source": [
        "## Data"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "dataset = load_dataset(\"Salesforce/dialogstudio\", \"TweetSumm\")\n",
        "dataset"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Kc0CVTtUkWvl",
        "outputId": "b078c12b-4a06-49e1-f101-3fdc40a7f5dd"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "DatasetDict({\n",
              "    train: Dataset({\n",
              "        features: ['original dialog id', 'new dialog id', 'dialog index', 'original dialog info', 'log', 'prompt'],\n",
              "        num_rows: 879\n",
              "    })\n",
              "    validation: Dataset({\n",
              "        features: ['original dialog id', 'new dialog id', 'dialog index', 'original dialog info', 'log', 'prompt'],\n",
              "        num_rows: 110\n",
              "    })\n",
              "    test: Dataset({\n",
              "        features: ['original dialog id', 'new dialog id', 'dialog index', 'original dialog info', 'log', 'prompt'],\n",
              "        num_rows: 110\n",
              "    })\n",
              "})"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "DEFAULT_SYSTEM_PROMPT = \"\"\"\n",
        "Below is a conversation between a human and an AI agent. Write a summary of the conversation.\n",
        "\"\"\".strip()\n",
        "\n",
        "\n",
        "def generate_training_prompt(\n",
        "    conversation: str, summary: str, system_prompt: str = DEFAULT_SYSTEM_PROMPT\n",
        ") -> str:\n",
        "    return f\"\"\"### Instruction: {system_prompt}\n",
        "\n",
        "### Input:\n",
        "{conversation.strip()}\n",
        "\n",
        "### Response:\n",
        "{summary}\n",
        "\"\"\".strip()"
      ],
      "metadata": {
        "id": "fbx71jhaMGK5"
      },
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def clean_text(text):\n",
        "    text = re.sub(r\"http\\S+\", \"\", text)\n",
        "    text = re.sub(r\"@[^\\s]+\", \"\", text)\n",
        "    text = re.sub(r\"\\s+\", \" \", text)\n",
        "    return re.sub(r\"\\^[^ ]+\", \"\", text)\n",
        "\n",
        "\n",
        "def create_conversation_text(data_point):\n",
        "    text = \"\"\n",
        "    for item in data_point[\"log\"]:\n",
        "        user = clean_text(item[\"user utterance\"])\n",
        "        text += f\"user: {user.strip()}\\n\"\n",
        "\n",
        "        agent = clean_text(item[\"system response\"])\n",
        "        text += f\"agent: {agent.strip()}\\n\"\n",
        "\n",
        "    return text"
      ],
      "metadata": {
        "id": "gMfzUJVOR9Lr"
      },
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def generate_text(data_point):\n",
        "    summaries = json.loads(data_point[\"original dialog info\"])[\"summaries\"][\n",
        "        \"abstractive_summaries\"\n",
        "    ]\n",
        "    summary = summaries[0]\n",
        "    summary = \" \".join(summary)\n",
        "\n",
        "    conversation_text = create_conversation_text(data_point)\n",
        "    return {\n",
        "        \"conversation\": conversation_text,\n",
        "        \"summary\": summary,\n",
        "        \"text\": generate_training_prompt(conversation_text, summary),\n",
        "    }"
      ],
      "metadata": {
        "id": "eRbskn48QNfW"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "example = generate_text(dataset[\"train\"][0])"
      ],
      "metadata": {
        "id": "J9VuGHGYSR5q"
      },
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(example[\"summary\"])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ycfL7LvHSu2h",
        "outputId": "0ed47942-4843-4427-de4d-92f37c84504e"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Customer enquired about his Iphone and Apple watch which is not showing his any steps/activity and health activities. Agent is asking to move to DM and look into it.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(example[\"conversation\"])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "eL7EDMq_SxlJ",
        "outputId": "946ec8e8-58a5-4afb-abfa-49a9239097d0"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "user: So neither my iPhone nor my Apple Watch are recording my steps/activity, and Health doesn’t recognise either source anymore for some reason. Any ideas? please read the above.\n",
            "agent: Let’s investigate this together. To start, can you tell us the software versions your iPhone and Apple Watch are running currently?\n",
            "user: My iPhone is on 11.1.2, and my watch is on 4.1.\n",
            "agent: Thank you. Have you tried restarting both devices since this started happening?\n",
            "user: I’ve restarted both, also un-paired then re-paired the watch.\n",
            "agent: Got it. When did you first notice that the two devices were not talking to each other. Do the two devices communicate through other apps such as Messages?\n",
            "user: Yes, everything seems fine, it’s just Health and activity.\n",
            "agent: Let’s move to DM and look into this a bit more. When reaching out in DM, let us know when this first started happening please. For example, did it start after an update or after installing a certain app?\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(example[\"text\"])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BbiL_o5dZZhg",
        "outputId": "af672c10-5160-4167-ad33-aeeea5b1ebbd"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "### Instruction: Below is a conversation between a human and an AI agent. Write a summary of the conversation.\n",
            "\n",
            "### Input:\n",
            "user: So neither my iPhone nor my Apple Watch are recording my steps/activity, and Health doesn’t recognise either source anymore for some reason. Any ideas? please read the above.\n",
            "agent: Let’s investigate this together. To start, can you tell us the software versions your iPhone and Apple Watch are running currently?\n",
            "user: My iPhone is on 11.1.2, and my watch is on 4.1.\n",
            "agent: Thank you. Have you tried restarting both devices since this started happening?\n",
            "user: I’ve restarted both, also un-paired then re-paired the watch.\n",
            "agent: Got it. When did you first notice that the two devices were not talking to each other. Do the two devices communicate through other apps such as Messages?\n",
            "user: Yes, everything seems fine, it’s just Health and activity.\n",
            "agent: Let’s move to DM and look into this a bit more. When reaching out in DM, let us know when this first started happening please. For example, did it start after an update or after installing a certain app?\n",
            "\n",
            "### Response:\n",
            "Customer enquired about his Iphone and Apple watch which is not showing his any steps/activity and health activities. Agent is asking to move to DM and look into it.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def process_dataset(data: Dataset):\n",
        "    return (\n",
        "        data.shuffle(seed=42)\n",
        "        .map(generate_text)\n",
        "        .remove_columns(\n",
        "            [\n",
        "                \"original dialog id\",\n",
        "                \"new dialog id\",\n",
        "                \"dialog index\",\n",
        "                \"original dialog info\",\n",
        "                \"log\",\n",
        "                \"prompt\",\n",
        "            ]\n",
        "        )\n",
        "    )"
      ],
      "metadata": {
        "id": "jKidKeUpZkPb"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "dataset[\"train\"] = process_dataset(dataset[\"train\"])\n",
        "dataset[\"validation\"] = process_dataset(dataset[\"validation\"])\n",
        "dataset[\"test\"] = process_dataset(dataset[\"test\"])"
      ],
      "metadata": {
        "id": "XHy1pVjlaLtm"
      },
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "usDeQuT2Wssl"
      },
      "source": [
        "## Model"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 24,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 145,
          "referenced_widgets": [
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            "3502bced8abc4cfc87300881857c4e08",
            "c726307cdc3c4598ad45879f3f29e60c"
          ]
        },
        "id": "3cLg8cYCdv74",
        "outputId": "b602a1eb-af6c-4069-a8f0-ee389e86ea38"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "VBox(children=(HTML(value='<center> <img\\nsrc=https://huggingface.co/front/assets/huggingface_logo-noborder.sv…"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "96ef5be98b5c4f2c9945b1a8c0989d7b"
            }
          },
          "metadata": {}
        }
      ],
      "source": [
        "notebook_login()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {
        "id": "GwxKEVnKWWss"
      },
      "outputs": [],
      "source": [
        "def create_model_and_tokenizer():\n",
        "    bnb_config = BitsAndBytesConfig(\n",
        "        load_in_4bit=True,\n",
        "        bnb_4bit_use_double_quant=True,\n",
        "        bnb_4bit_quant_type=\"nf4\",\n",
        "        bnb_4bit_compute_dtype=torch.float16,\n",
        "    )\n",
        "\n",
        "    model = AutoModelForCausalLM.from_pretrained(\n",
        "        MODEL_NAME,\n",
        "        device_map={\"\":0},\n",
        "        trust_remote_code=True,\n",
        "        quantization_config=bnb_config\n",
        "    )\n",
        "\n",
        "    tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)\n",
        "    tokenizer.pad_token = tokenizer.eos_token\n",
        "\n",
        "    return model, tokenizer"
      ]
    },
    {
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        },
        "id": "qDVlGrUmdzdh",
        "outputId": "d068211c-3c4f-437e-855e-a4e721997466"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
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          "metadata": {}
        },
        {
          "output_type": "display_data",
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          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "A new version of the following files was downloaded from https://huggingface.co/microsoft/phi-1_5:\n",
            "- configuration_mixformer_sequential.py\n",
            ". Make sure to double-check they do not contain any added malicious code. To avoid downloading new versions of the code file, you can pin a revision.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
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            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "A new version of the following files was downloaded from https://huggingface.co/microsoft/phi-1_5:\n",
            "- modeling_mixformer_sequential.py\n",
            ". Make sure to double-check they do not contain any added malicious code. To avoid downloading new versions of the code file, you can pin a revision.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
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          },
          "metadata": {}
        },
        {
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          "metadata": {}
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          "metadata": {}
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          },
          "metadata": {}
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        {
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "cae6be4ca33c48acb53cfcad9cbad985"
            }
          },
          "metadata": {}
        }
      ],
      "source": [
        "model, tokenizer = create_model_and_tokenizer()\n",
        "model.config.use_cache = False"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DRubXChbe7pL",
        "outputId": "41c5c6ca-e714-4cdb-fb33-42be895eb19d"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'quant_method': <QuantizationMethod.BITS_AND_BYTES: 'bitsandbytes'>,\n",
              " 'load_in_8bit': False,\n",
              " 'load_in_4bit': True,\n",
              " 'llm_int8_threshold': 6.0,\n",
              " 'llm_int8_skip_modules': None,\n",
              " 'llm_int8_enable_fp32_cpu_offload': False,\n",
              " 'llm_int8_has_fp16_weight': False,\n",
              " 'bnb_4bit_quant_type': 'nf4',\n",
              " 'bnb_4bit_use_double_quant': True,\n",
              " 'bnb_4bit_compute_dtype': 'float16'}"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ],
      "source": [
        "model.config.quantization_config.to_dict()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 19,
      "metadata": {
        "id": "1Sj65mDxNeJv"
      },
      "outputs": [],
      "source": [
        "peft_config = LoraConfig(\n",
        "    r=16,\n",
        "    lora_alpha=16,\n",
        "    target_modules=[\"Wqkv\", \"out_proj\"],\n",
        "    lora_dropout=0.05,\n",
        "    bias=\"none\",\n",
        "    task_type=\"CAUSAL_LM\"\n",
        ")"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model = get_peft_model(model, peft_config)\n",
        "model.print_trainable_parameters()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Vv11jEAJT9Pp",
        "outputId": "83cb3d0e-df99-4dad-f46a-cd19fe571130"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "trainable params: 4,718,592 || all params: 1,422,989,312 || trainable%: 0.3315971497613047\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vVSLIcQl8g9h"
      },
      "source": [
        "## Training"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 21,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 821
        },
        "id": "0FoXB0psS8hN",
        "outputId": "10d07019-3644-4b3f-8eff-230c7dba6af0"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.Javascript object>"
            ],
            "application/javascript": [
              "\n",
              "        (async () => {\n",
              "            const url = new URL(await google.colab.kernel.proxyPort(6006, {'cache': true}));\n",
              "            url.searchParams.set('tensorboardColab', 'true');\n",
              "            const iframe = document.createElement('iframe');\n",
              "            iframe.src = url;\n",
              "            iframe.setAttribute('width', '100%');\n",
              "            iframe.setAttribute('height', '800');\n",
              "            iframe.setAttribute('frameborder', 0);\n",
              "            document.body.appendChild(iframe);\n",
              "        })();\n",
              "    "
            ]
          },
          "metadata": {}
        }
      ],
      "source": [
        "OUTPUT_DIR = \"experiments\"\n",
        "\n",
        "%load_ext tensorboard\n",
        "%tensorboard --logdir experiments/runs"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 22,
      "metadata": {
        "id": "gIoe9TqOof-V"
      },
      "outputs": [],
      "source": [
        "training_arguments = TrainingArguments(\n",
        "        output_dir=\"phi-1_5-finetuned-dialogstudio\",\n",
        "        per_device_train_batch_size=4,\n",
        "        gradient_accumulation_steps=1,\n",
        "        learning_rate=2e-4,\n",
        "        lr_scheduler_type=\"cosine\",\n",
        "        save_strategy=\"epoch\",\n",
        "        logging_steps=1,\n",
        "        max_steps=3,\n",
        "        num_train_epochs=1,\n",
        "        push_to_hub=True\n",
        "    )"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 25,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZL4Qa_cypL1f",
        "outputId": "7d3c3821-8395-407c-8f95-1dbd1d479efb"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/trl/trainer/sft_trainer.py:166: UserWarning: You didn't pass a `max_seq_length` argument to the SFTTrainer, this will default to 1024\n",
            "  warnings.warn(\n"
          ]
        }
      ],
      "source": [
        "trainer = SFTTrainer(\n",
        "    model=model,\n",
        "    train_dataset=dataset[\"train\"],\n",
        "    eval_dataset=dataset[\"validation\"],\n",
        "    peft_config=peft_config,\n",
        "    dataset_text_field=\"text\",\n",
        "    tokenizer=tokenizer,\n",
        "    args=training_arguments,\n",
        ")"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "trainer.train()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 241
        },
        "id": "y7LDwR6kJdkO",
        "outputId": "e22ee88f-7c55-4251-8a3e-22bf75e5c777"
      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "You're using a CodeGenTokenizerFast tokenizer. Please note that with a fast tokenizer, using the `__call__` method is faster than using a method to encode the text followed by a call to the `pad` method to get a padded encoding.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "\n",
              "    <div>\n",
              "      \n",
              "      <progress value='3' max='3' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
              "      [3/3 00:02, Epoch 0/1]\n",
              "    </div>\n",
              "    <table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              " <tr style=\"text-align: left;\">\n",
              "      <th>Step</th>\n",
              "      <th>Training Loss</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <td>1</td>\n",
              "      <td>3.080800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>2</td>\n",
              "      <td>2.887100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>3</td>\n",
              "      <td>3.302700</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table><p>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "TrainOutput(global_step=3, training_loss=3.090197483698527, metrics={'train_runtime': 7.7717, 'train_samples_per_second': 1.544, 'train_steps_per_second': 0.386, 'total_flos': 22418657574912.0, 'train_loss': 3.090197483698527, 'epoch': 0.01})"
            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "trainer.evaluate()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 124
        },
        "id": "IRiQABpzeom6",
        "outputId": "4e1c2f58-5f5f-4322-86a7-6df3a779223a"
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "\n",
              "    <div>\n",
              "      \n",
              "      <progress value='14' max='14' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
              "      [14/14 00:11]\n",
              "    </div>\n",
              "    "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'eval_loss': 3.243016242980957,\n",
              " 'eval_runtime': 12.0781,\n",
              " 'eval_samples_per_second': 9.107,\n",
              " 'eval_steps_per_second': 1.159,\n",
              " 'epoch': 0.01}"
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "trainer.push_to_hub()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "ZCBJa6mZaSv7",
        "outputId": "7111feef-c4e3-4330-b291-437c19c41c33"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'https://huggingface.co/ashishpatel26/phi-1_5-finetuned-dialogstudio/tree/main/'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "trainer.save_model(\"phi-1_5-finetuned-dialogstudio\")"
      ],
      "metadata": {
        "id": "jJdkDvxKOq8P"
      },
      "execution_count": 30,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": 30,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WywDQRmGEVOJ",
        "outputId": "acdd8465-32e1-4fc1-ad75-06831edf8d85"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "PeftModelForCausalLM(\n",
              "  (base_model): LoraModel(\n",
              "    (model): MixFormerSequentialForCausalLM(\n",
              "      (layers): Sequential(\n",
              "        (0): Embedding(\n",
              "          (wte): Embedding(51200, 2048)\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "        (1): ParallelBlock(\n",
              "          (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "          (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "          (mixer): MHA(\n",
              "            (rotary_emb): RotaryEmbedding()\n",
              "            (Wqkv): Linear4bit(\n",
              "              in_features=2048, out_features=6144, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=6144, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (out_proj): Linear4bit(\n",
              "              in_features=2048, out_features=2048, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=2048, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (inner_attn): SelfAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "            (inner_cross_attn): CrossAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "          )\n",
              "          (mlp): MLP(\n",
              "            (fc1): Linear4bit(in_features=2048, out_features=8192, bias=True)\n",
              "            (fc2): Linear4bit(in_features=8192, out_features=2048, bias=True)\n",
              "            (act): NewGELUActivation()\n",
              "          )\n",
              "        )\n",
              "        (2): ParallelBlock(\n",
              "          (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "          (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "          (mixer): MHA(\n",
              "            (rotary_emb): RotaryEmbedding()\n",
              "            (Wqkv): Linear4bit(\n",
              "              in_features=2048, out_features=6144, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=6144, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (out_proj): Linear4bit(\n",
              "              in_features=2048, out_features=2048, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=2048, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (inner_attn): SelfAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "            (inner_cross_attn): CrossAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "          )\n",
              "          (mlp): MLP(\n",
              "            (fc1): Linear4bit(in_features=2048, out_features=8192, bias=True)\n",
              "            (fc2): Linear4bit(in_features=8192, out_features=2048, bias=True)\n",
              "            (act): NewGELUActivation()\n",
              "          )\n",
              "        )\n",
              "        (3): ParallelBlock(\n",
              "          (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "          (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "          (mixer): MHA(\n",
              "            (rotary_emb): RotaryEmbedding()\n",
              "            (Wqkv): Linear4bit(\n",
              "              in_features=2048, out_features=6144, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=6144, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (out_proj): Linear4bit(\n",
              "              in_features=2048, out_features=2048, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=2048, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (inner_attn): SelfAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "            (inner_cross_attn): CrossAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "          )\n",
              "          (mlp): MLP(\n",
              "            (fc1): Linear4bit(in_features=2048, out_features=8192, bias=True)\n",
              "            (fc2): Linear4bit(in_features=8192, out_features=2048, bias=True)\n",
              "            (act): NewGELUActivation()\n",
              "          )\n",
              "        )\n",
              "        (4): ParallelBlock(\n",
              "          (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "          (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "          (mixer): MHA(\n",
              "            (rotary_emb): RotaryEmbedding()\n",
              "            (Wqkv): Linear4bit(\n",
              "              in_features=2048, out_features=6144, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=6144, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (out_proj): Linear4bit(\n",
              "              in_features=2048, out_features=2048, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=2048, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (inner_attn): SelfAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "            (inner_cross_attn): CrossAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "          )\n",
              "          (mlp): MLP(\n",
              "            (fc1): Linear4bit(in_features=2048, out_features=8192, bias=True)\n",
              "            (fc2): Linear4bit(in_features=8192, out_features=2048, bias=True)\n",
              "            (act): NewGELUActivation()\n",
              "          )\n",
              "        )\n",
              "        (5): ParallelBlock(\n",
              "          (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "          (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "          (mixer): MHA(\n",
              "            (rotary_emb): RotaryEmbedding()\n",
              "            (Wqkv): Linear4bit(\n",
              "              in_features=2048, out_features=6144, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=6144, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (out_proj): Linear4bit(\n",
              "              in_features=2048, out_features=2048, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=2048, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (inner_attn): SelfAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "            (inner_cross_attn): CrossAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "          )\n",
              "          (mlp): MLP(\n",
              "            (fc1): Linear4bit(in_features=2048, out_features=8192, bias=True)\n",
              "            (fc2): Linear4bit(in_features=8192, out_features=2048, bias=True)\n",
              "            (act): NewGELUActivation()\n",
              "          )\n",
              "        )\n",
              "        (6): ParallelBlock(\n",
              "          (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "          (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "          (mixer): MHA(\n",
              "            (rotary_emb): RotaryEmbedding()\n",
              "            (Wqkv): Linear4bit(\n",
              "              in_features=2048, out_features=6144, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=6144, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (out_proj): Linear4bit(\n",
              "              in_features=2048, out_features=2048, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=2048, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (inner_attn): SelfAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "            (inner_cross_attn): CrossAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "          )\n",
              "          (mlp): MLP(\n",
              "            (fc1): Linear4bit(in_features=2048, out_features=8192, bias=True)\n",
              "            (fc2): Linear4bit(in_features=8192, out_features=2048, bias=True)\n",
              "            (act): NewGELUActivation()\n",
              "          )\n",
              "        )\n",
              "        (7): ParallelBlock(\n",
              "          (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "          (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "          (mixer): MHA(\n",
              "            (rotary_emb): RotaryEmbedding()\n",
              "            (Wqkv): Linear4bit(\n",
              "              in_features=2048, out_features=6144, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=6144, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (out_proj): Linear4bit(\n",
              "              in_features=2048, out_features=2048, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=2048, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (inner_attn): SelfAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "            (inner_cross_attn): CrossAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "          )\n",
              "          (mlp): MLP(\n",
              "            (fc1): Linear4bit(in_features=2048, out_features=8192, bias=True)\n",
              "            (fc2): Linear4bit(in_features=8192, out_features=2048, bias=True)\n",
              "            (act): NewGELUActivation()\n",
              "          )\n",
              "        )\n",
              "        (8): ParallelBlock(\n",
              "          (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "          (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "          (mixer): MHA(\n",
              "            (rotary_emb): RotaryEmbedding()\n",
              "            (Wqkv): Linear4bit(\n",
              "              in_features=2048, out_features=6144, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=6144, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (out_proj): Linear4bit(\n",
              "              in_features=2048, out_features=2048, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=2048, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (inner_attn): SelfAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "            (inner_cross_attn): CrossAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "          )\n",
              "          (mlp): MLP(\n",
              "            (fc1): Linear4bit(in_features=2048, out_features=8192, bias=True)\n",
              "            (fc2): Linear4bit(in_features=8192, out_features=2048, bias=True)\n",
              "            (act): NewGELUActivation()\n",
              "          )\n",
              "        )\n",
              "        (9): ParallelBlock(\n",
              "          (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "          (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "          (mixer): MHA(\n",
              "            (rotary_emb): RotaryEmbedding()\n",
              "            (Wqkv): Linear4bit(\n",
              "              in_features=2048, out_features=6144, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=6144, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (out_proj): Linear4bit(\n",
              "              in_features=2048, out_features=2048, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=2048, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (inner_attn): SelfAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "            (inner_cross_attn): CrossAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "          )\n",
              "          (mlp): MLP(\n",
              "            (fc1): Linear4bit(in_features=2048, out_features=8192, bias=True)\n",
              "            (fc2): Linear4bit(in_features=8192, out_features=2048, bias=True)\n",
              "            (act): NewGELUActivation()\n",
              "          )\n",
              "        )\n",
              "        (10): ParallelBlock(\n",
              "          (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "          (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "          (mixer): MHA(\n",
              "            (rotary_emb): RotaryEmbedding()\n",
              "            (Wqkv): Linear4bit(\n",
              "              in_features=2048, out_features=6144, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=6144, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (out_proj): Linear4bit(\n",
              "              in_features=2048, out_features=2048, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=2048, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (inner_attn): SelfAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "            (inner_cross_attn): CrossAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "          )\n",
              "          (mlp): MLP(\n",
              "            (fc1): Linear4bit(in_features=2048, out_features=8192, bias=True)\n",
              "            (fc2): Linear4bit(in_features=8192, out_features=2048, bias=True)\n",
              "            (act): NewGELUActivation()\n",
              "          )\n",
              "        )\n",
              "        (11): ParallelBlock(\n",
              "          (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "          (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "          (mixer): MHA(\n",
              "            (rotary_emb): RotaryEmbedding()\n",
              "            (Wqkv): Linear4bit(\n",
              "              in_features=2048, out_features=6144, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=6144, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (out_proj): Linear4bit(\n",
              "              in_features=2048, out_features=2048, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=2048, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (inner_attn): SelfAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "            (inner_cross_attn): CrossAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "          )\n",
              "          (mlp): MLP(\n",
              "            (fc1): Linear4bit(in_features=2048, out_features=8192, bias=True)\n",
              "            (fc2): Linear4bit(in_features=8192, out_features=2048, bias=True)\n",
              "            (act): NewGELUActivation()\n",
              "          )\n",
              "        )\n",
              "        (12): ParallelBlock(\n",
              "          (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "          (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "          (mixer): MHA(\n",
              "            (rotary_emb): RotaryEmbedding()\n",
              "            (Wqkv): Linear4bit(\n",
              "              in_features=2048, out_features=6144, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=6144, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (out_proj): Linear4bit(\n",
              "              in_features=2048, out_features=2048, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=2048, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (inner_attn): SelfAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "            (inner_cross_attn): CrossAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "          )\n",
              "          (mlp): MLP(\n",
              "            (fc1): Linear4bit(in_features=2048, out_features=8192, bias=True)\n",
              "            (fc2): Linear4bit(in_features=8192, out_features=2048, bias=True)\n",
              "            (act): NewGELUActivation()\n",
              "          )\n",
              "        )\n",
              "        (13): ParallelBlock(\n",
              "          (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "          (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "          (mixer): MHA(\n",
              "            (rotary_emb): RotaryEmbedding()\n",
              "            (Wqkv): Linear4bit(\n",
              "              in_features=2048, out_features=6144, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=6144, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (out_proj): Linear4bit(\n",
              "              in_features=2048, out_features=2048, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=2048, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (inner_attn): SelfAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "            (inner_cross_attn): CrossAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "          )\n",
              "          (mlp): MLP(\n",
              "            (fc1): Linear4bit(in_features=2048, out_features=8192, bias=True)\n",
              "            (fc2): Linear4bit(in_features=8192, out_features=2048, bias=True)\n",
              "            (act): NewGELUActivation()\n",
              "          )\n",
              "        )\n",
              "        (14): ParallelBlock(\n",
              "          (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "          (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "          (mixer): MHA(\n",
              "            (rotary_emb): RotaryEmbedding()\n",
              "            (Wqkv): Linear4bit(\n",
              "              in_features=2048, out_features=6144, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=6144, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (out_proj): Linear4bit(\n",
              "              in_features=2048, out_features=2048, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=2048, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (inner_attn): SelfAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "            (inner_cross_attn): CrossAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "          )\n",
              "          (mlp): MLP(\n",
              "            (fc1): Linear4bit(in_features=2048, out_features=8192, bias=True)\n",
              "            (fc2): Linear4bit(in_features=8192, out_features=2048, bias=True)\n",
              "            (act): NewGELUActivation()\n",
              "          )\n",
              "        )\n",
              "        (15): ParallelBlock(\n",
              "          (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "          (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "          (mixer): MHA(\n",
              "            (rotary_emb): RotaryEmbedding()\n",
              "            (Wqkv): Linear4bit(\n",
              "              in_features=2048, out_features=6144, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=6144, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (out_proj): Linear4bit(\n",
              "              in_features=2048, out_features=2048, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=2048, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (inner_attn): SelfAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "            (inner_cross_attn): CrossAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "          )\n",
              "          (mlp): MLP(\n",
              "            (fc1): Linear4bit(in_features=2048, out_features=8192, bias=True)\n",
              "            (fc2): Linear4bit(in_features=8192, out_features=2048, bias=True)\n",
              "            (act): NewGELUActivation()\n",
              "          )\n",
              "        )\n",
              "        (16): ParallelBlock(\n",
              "          (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "          (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "          (mixer): MHA(\n",
              "            (rotary_emb): RotaryEmbedding()\n",
              "            (Wqkv): Linear4bit(\n",
              "              in_features=2048, out_features=6144, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=6144, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (out_proj): Linear4bit(\n",
              "              in_features=2048, out_features=2048, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=2048, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (inner_attn): SelfAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "            (inner_cross_attn): CrossAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "          )\n",
              "          (mlp): MLP(\n",
              "            (fc1): Linear4bit(in_features=2048, out_features=8192, bias=True)\n",
              "            (fc2): Linear4bit(in_features=8192, out_features=2048, bias=True)\n",
              "            (act): NewGELUActivation()\n",
              "          )\n",
              "        )\n",
              "        (17): ParallelBlock(\n",
              "          (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "          (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "          (mixer): MHA(\n",
              "            (rotary_emb): RotaryEmbedding()\n",
              "            (Wqkv): Linear4bit(\n",
              "              in_features=2048, out_features=6144, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=6144, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (out_proj): Linear4bit(\n",
              "              in_features=2048, out_features=2048, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=2048, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (inner_attn): SelfAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "            (inner_cross_attn): CrossAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "          )\n",
              "          (mlp): MLP(\n",
              "            (fc1): Linear4bit(in_features=2048, out_features=8192, bias=True)\n",
              "            (fc2): Linear4bit(in_features=8192, out_features=2048, bias=True)\n",
              "            (act): NewGELUActivation()\n",
              "          )\n",
              "        )\n",
              "        (18): ParallelBlock(\n",
              "          (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "          (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "          (mixer): MHA(\n",
              "            (rotary_emb): RotaryEmbedding()\n",
              "            (Wqkv): Linear4bit(\n",
              "              in_features=2048, out_features=6144, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=6144, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (out_proj): Linear4bit(\n",
              "              in_features=2048, out_features=2048, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=2048, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (inner_attn): SelfAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "            (inner_cross_attn): CrossAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "          )\n",
              "          (mlp): MLP(\n",
              "            (fc1): Linear4bit(in_features=2048, out_features=8192, bias=True)\n",
              "            (fc2): Linear4bit(in_features=8192, out_features=2048, bias=True)\n",
              "            (act): NewGELUActivation()\n",
              "          )\n",
              "        )\n",
              "        (19): ParallelBlock(\n",
              "          (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "          (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "          (mixer): MHA(\n",
              "            (rotary_emb): RotaryEmbedding()\n",
              "            (Wqkv): Linear4bit(\n",
              "              in_features=2048, out_features=6144, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=6144, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (out_proj): Linear4bit(\n",
              "              in_features=2048, out_features=2048, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=2048, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (inner_attn): SelfAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "            (inner_cross_attn): CrossAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "          )\n",
              "          (mlp): MLP(\n",
              "            (fc1): Linear4bit(in_features=2048, out_features=8192, bias=True)\n",
              "            (fc2): Linear4bit(in_features=8192, out_features=2048, bias=True)\n",
              "            (act): NewGELUActivation()\n",
              "          )\n",
              "        )\n",
              "        (20): ParallelBlock(\n",
              "          (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "          (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "          (mixer): MHA(\n",
              "            (rotary_emb): RotaryEmbedding()\n",
              "            (Wqkv): Linear4bit(\n",
              "              in_features=2048, out_features=6144, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=6144, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (out_proj): Linear4bit(\n",
              "              in_features=2048, out_features=2048, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=2048, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (inner_attn): SelfAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "            (inner_cross_attn): CrossAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "          )\n",
              "          (mlp): MLP(\n",
              "            (fc1): Linear4bit(in_features=2048, out_features=8192, bias=True)\n",
              "            (fc2): Linear4bit(in_features=8192, out_features=2048, bias=True)\n",
              "            (act): NewGELUActivation()\n",
              "          )\n",
              "        )\n",
              "        (21): ParallelBlock(\n",
              "          (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "          (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "          (mixer): MHA(\n",
              "            (rotary_emb): RotaryEmbedding()\n",
              "            (Wqkv): Linear4bit(\n",
              "              in_features=2048, out_features=6144, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=6144, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (out_proj): Linear4bit(\n",
              "              in_features=2048, out_features=2048, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=2048, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (inner_attn): SelfAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "            (inner_cross_attn): CrossAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "          )\n",
              "          (mlp): MLP(\n",
              "            (fc1): Linear4bit(in_features=2048, out_features=8192, bias=True)\n",
              "            (fc2): Linear4bit(in_features=8192, out_features=2048, bias=True)\n",
              "            (act): NewGELUActivation()\n",
              "          )\n",
              "        )\n",
              "        (22): ParallelBlock(\n",
              "          (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "          (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "          (mixer): MHA(\n",
              "            (rotary_emb): RotaryEmbedding()\n",
              "            (Wqkv): Linear4bit(\n",
              "              in_features=2048, out_features=6144, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=6144, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (out_proj): Linear4bit(\n",
              "              in_features=2048, out_features=2048, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=2048, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (inner_attn): SelfAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "            (inner_cross_attn): CrossAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "          )\n",
              "          (mlp): MLP(\n",
              "            (fc1): Linear4bit(in_features=2048, out_features=8192, bias=True)\n",
              "            (fc2): Linear4bit(in_features=8192, out_features=2048, bias=True)\n",
              "            (act): NewGELUActivation()\n",
              "          )\n",
              "        )\n",
              "        (23): ParallelBlock(\n",
              "          (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "          (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "          (mixer): MHA(\n",
              "            (rotary_emb): RotaryEmbedding()\n",
              "            (Wqkv): Linear4bit(\n",
              "              in_features=2048, out_features=6144, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=6144, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (out_proj): Linear4bit(\n",
              "              in_features=2048, out_features=2048, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=2048, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (inner_attn): SelfAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "            (inner_cross_attn): CrossAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "          )\n",
              "          (mlp): MLP(\n",
              "            (fc1): Linear4bit(in_features=2048, out_features=8192, bias=True)\n",
              "            (fc2): Linear4bit(in_features=8192, out_features=2048, bias=True)\n",
              "            (act): NewGELUActivation()\n",
              "          )\n",
              "        )\n",
              "        (24): ParallelBlock(\n",
              "          (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "          (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "          (mixer): MHA(\n",
              "            (rotary_emb): RotaryEmbedding()\n",
              "            (Wqkv): Linear4bit(\n",
              "              in_features=2048, out_features=6144, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=6144, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (out_proj): Linear4bit(\n",
              "              in_features=2048, out_features=2048, bias=True\n",
              "              (lora_dropout): ModuleDict(\n",
              "                (default): Dropout(p=0.05, inplace=False)\n",
              "              )\n",
              "              (lora_A): ModuleDict(\n",
              "                (default): Linear(in_features=2048, out_features=16, bias=False)\n",
              "              )\n",
              "              (lora_B): ModuleDict(\n",
              "                (default): Linear(in_features=16, out_features=2048, bias=False)\n",
              "              )\n",
              "              (lora_embedding_A): ParameterDict()\n",
              "              (lora_embedding_B): ParameterDict()\n",
              "            )\n",
              "            (inner_attn): SelfAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "            (inner_cross_attn): CrossAttention(\n",
              "              (drop): Dropout(p=0.0, inplace=False)\n",
              "            )\n",
              "          )\n",
              "          (mlp): MLP(\n",
              "            (fc1): Linear4bit(in_features=2048, out_features=8192, bias=True)\n",
              "            (fc2): Linear4bit(in_features=8192, out_features=2048, bias=True)\n",
              "            (act): NewGELUActivation()\n",
              "          )\n",
              "        )\n",
              "        (25): CausalLMHead(\n",
              "          (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "          (linear): Linear(in_features=2048, out_features=51200, bias=True)\n",
              "        )\n",
              "      )\n",
              "      (loss): CausalLMLoss(\n",
              "        (loss_fct): CrossEntropyLoss()\n",
              "      )\n",
              "    )\n",
              "  )\n",
              ")"
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ],
      "source": [
        "trainer.model"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Inference"
      ],
      "metadata": {
        "id": "7lSxtsWehGcy"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from peft import PeftModel\n",
        "from transformers import AutoModelForCausalLM\n",
        "import torch\n",
        "model = AutoModelForCausalLM.from_pretrained(\"microsoft/phi-1_5\", trust_remote_code=True, torch_dtype=torch.float32)\n",
        "peft_model = PeftModel.from_pretrained(model, \"ashishpatel26/phi-1_5-finetuned-dialogstudio\", from_transformers=True)\n",
        "model = peft_model.merge_and_unload()\n",
        "model"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000,
          "referenced_widgets": [
            "18d7c57661f54a2f906b86e5b92a356d",
            "e132669f57024ebcadc1f0d3899fbda2",
            "f3e78fd1331b4463a243475e12bd2480",
            "386c7bc116b849aaa2bd4c8b0c27b0e9",
            "4385c5f8fc5d4d179e02ebf65aae4e0f",
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        },
        "id": "e43OUEfYOzFF",
        "outputId": "76eec92a-79aa-41af-de41-63b60483470c"
      },
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)/adapter_config.json:   0%|          | 0.00/440 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "18d7c57661f54a2f906b86e5b92a356d"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading adapter_model.bin:   0%|          | 0.00/18.9M [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "31405710033848009cf8227a7611864f"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "MixFormerSequentialForCausalLM(\n",
              "  (layers): Sequential(\n",
              "    (0): Embedding(\n",
              "      (wte): Embedding(51200, 2048)\n",
              "      (drop): Dropout(p=0.0, inplace=False)\n",
              "    )\n",
              "    (1): ParallelBlock(\n",
              "      (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "      (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "      (mixer): MHA(\n",
              "        (rotary_emb): RotaryEmbedding()\n",
              "        (Wqkv): Linear(in_features=2048, out_features=6144, bias=True)\n",
              "        (out_proj): Linear(in_features=2048, out_features=2048, bias=True)\n",
              "        (inner_attn): SelfAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "        (inner_cross_attn): CrossAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (mlp): MLP(\n",
              "        (fc1): Linear(in_features=2048, out_features=8192, bias=True)\n",
              "        (fc2): Linear(in_features=8192, out_features=2048, bias=True)\n",
              "        (act): NewGELUActivation()\n",
              "      )\n",
              "    )\n",
              "    (2): ParallelBlock(\n",
              "      (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "      (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "      (mixer): MHA(\n",
              "        (rotary_emb): RotaryEmbedding()\n",
              "        (Wqkv): Linear(in_features=2048, out_features=6144, bias=True)\n",
              "        (out_proj): Linear(in_features=2048, out_features=2048, bias=True)\n",
              "        (inner_attn): SelfAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "        (inner_cross_attn): CrossAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (mlp): MLP(\n",
              "        (fc1): Linear(in_features=2048, out_features=8192, bias=True)\n",
              "        (fc2): Linear(in_features=8192, out_features=2048, bias=True)\n",
              "        (act): NewGELUActivation()\n",
              "      )\n",
              "    )\n",
              "    (3): ParallelBlock(\n",
              "      (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "      (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "      (mixer): MHA(\n",
              "        (rotary_emb): RotaryEmbedding()\n",
              "        (Wqkv): Linear(in_features=2048, out_features=6144, bias=True)\n",
              "        (out_proj): Linear(in_features=2048, out_features=2048, bias=True)\n",
              "        (inner_attn): SelfAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "        (inner_cross_attn): CrossAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (mlp): MLP(\n",
              "        (fc1): Linear(in_features=2048, out_features=8192, bias=True)\n",
              "        (fc2): Linear(in_features=8192, out_features=2048, bias=True)\n",
              "        (act): NewGELUActivation()\n",
              "      )\n",
              "    )\n",
              "    (4): ParallelBlock(\n",
              "      (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "      (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "      (mixer): MHA(\n",
              "        (rotary_emb): RotaryEmbedding()\n",
              "        (Wqkv): Linear(in_features=2048, out_features=6144, bias=True)\n",
              "        (out_proj): Linear(in_features=2048, out_features=2048, bias=True)\n",
              "        (inner_attn): SelfAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "        (inner_cross_attn): CrossAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (mlp): MLP(\n",
              "        (fc1): Linear(in_features=2048, out_features=8192, bias=True)\n",
              "        (fc2): Linear(in_features=8192, out_features=2048, bias=True)\n",
              "        (act): NewGELUActivation()\n",
              "      )\n",
              "    )\n",
              "    (5): ParallelBlock(\n",
              "      (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "      (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "      (mixer): MHA(\n",
              "        (rotary_emb): RotaryEmbedding()\n",
              "        (Wqkv): Linear(in_features=2048, out_features=6144, bias=True)\n",
              "        (out_proj): Linear(in_features=2048, out_features=2048, bias=True)\n",
              "        (inner_attn): SelfAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "        (inner_cross_attn): CrossAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (mlp): MLP(\n",
              "        (fc1): Linear(in_features=2048, out_features=8192, bias=True)\n",
              "        (fc2): Linear(in_features=8192, out_features=2048, bias=True)\n",
              "        (act): NewGELUActivation()\n",
              "      )\n",
              "    )\n",
              "    (6): ParallelBlock(\n",
              "      (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "      (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "      (mixer): MHA(\n",
              "        (rotary_emb): RotaryEmbedding()\n",
              "        (Wqkv): Linear(in_features=2048, out_features=6144, bias=True)\n",
              "        (out_proj): Linear(in_features=2048, out_features=2048, bias=True)\n",
              "        (inner_attn): SelfAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "        (inner_cross_attn): CrossAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (mlp): MLP(\n",
              "        (fc1): Linear(in_features=2048, out_features=8192, bias=True)\n",
              "        (fc2): Linear(in_features=8192, out_features=2048, bias=True)\n",
              "        (act): NewGELUActivation()\n",
              "      )\n",
              "    )\n",
              "    (7): ParallelBlock(\n",
              "      (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "      (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "      (mixer): MHA(\n",
              "        (rotary_emb): RotaryEmbedding()\n",
              "        (Wqkv): Linear(in_features=2048, out_features=6144, bias=True)\n",
              "        (out_proj): Linear(in_features=2048, out_features=2048, bias=True)\n",
              "        (inner_attn): SelfAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "        (inner_cross_attn): CrossAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (mlp): MLP(\n",
              "        (fc1): Linear(in_features=2048, out_features=8192, bias=True)\n",
              "        (fc2): Linear(in_features=8192, out_features=2048, bias=True)\n",
              "        (act): NewGELUActivation()\n",
              "      )\n",
              "    )\n",
              "    (8): ParallelBlock(\n",
              "      (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "      (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "      (mixer): MHA(\n",
              "        (rotary_emb): RotaryEmbedding()\n",
              "        (Wqkv): Linear(in_features=2048, out_features=6144, bias=True)\n",
              "        (out_proj): Linear(in_features=2048, out_features=2048, bias=True)\n",
              "        (inner_attn): SelfAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "        (inner_cross_attn): CrossAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (mlp): MLP(\n",
              "        (fc1): Linear(in_features=2048, out_features=8192, bias=True)\n",
              "        (fc2): Linear(in_features=8192, out_features=2048, bias=True)\n",
              "        (act): NewGELUActivation()\n",
              "      )\n",
              "    )\n",
              "    (9): ParallelBlock(\n",
              "      (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "      (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "      (mixer): MHA(\n",
              "        (rotary_emb): RotaryEmbedding()\n",
              "        (Wqkv): Linear(in_features=2048, out_features=6144, bias=True)\n",
              "        (out_proj): Linear(in_features=2048, out_features=2048, bias=True)\n",
              "        (inner_attn): SelfAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "        (inner_cross_attn): CrossAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (mlp): MLP(\n",
              "        (fc1): Linear(in_features=2048, out_features=8192, bias=True)\n",
              "        (fc2): Linear(in_features=8192, out_features=2048, bias=True)\n",
              "        (act): NewGELUActivation()\n",
              "      )\n",
              "    )\n",
              "    (10): ParallelBlock(\n",
              "      (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "      (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "      (mixer): MHA(\n",
              "        (rotary_emb): RotaryEmbedding()\n",
              "        (Wqkv): Linear(in_features=2048, out_features=6144, bias=True)\n",
              "        (out_proj): Linear(in_features=2048, out_features=2048, bias=True)\n",
              "        (inner_attn): SelfAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "        (inner_cross_attn): CrossAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (mlp): MLP(\n",
              "        (fc1): Linear(in_features=2048, out_features=8192, bias=True)\n",
              "        (fc2): Linear(in_features=8192, out_features=2048, bias=True)\n",
              "        (act): NewGELUActivation()\n",
              "      )\n",
              "    )\n",
              "    (11): ParallelBlock(\n",
              "      (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "      (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "      (mixer): MHA(\n",
              "        (rotary_emb): RotaryEmbedding()\n",
              "        (Wqkv): Linear(in_features=2048, out_features=6144, bias=True)\n",
              "        (out_proj): Linear(in_features=2048, out_features=2048, bias=True)\n",
              "        (inner_attn): SelfAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "        (inner_cross_attn): CrossAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (mlp): MLP(\n",
              "        (fc1): Linear(in_features=2048, out_features=8192, bias=True)\n",
              "        (fc2): Linear(in_features=8192, out_features=2048, bias=True)\n",
              "        (act): NewGELUActivation()\n",
              "      )\n",
              "    )\n",
              "    (12): ParallelBlock(\n",
              "      (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "      (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "      (mixer): MHA(\n",
              "        (rotary_emb): RotaryEmbedding()\n",
              "        (Wqkv): Linear(in_features=2048, out_features=6144, bias=True)\n",
              "        (out_proj): Linear(in_features=2048, out_features=2048, bias=True)\n",
              "        (inner_attn): SelfAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "        (inner_cross_attn): CrossAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (mlp): MLP(\n",
              "        (fc1): Linear(in_features=2048, out_features=8192, bias=True)\n",
              "        (fc2): Linear(in_features=8192, out_features=2048, bias=True)\n",
              "        (act): NewGELUActivation()\n",
              "      )\n",
              "    )\n",
              "    (13): ParallelBlock(\n",
              "      (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "      (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "      (mixer): MHA(\n",
              "        (rotary_emb): RotaryEmbedding()\n",
              "        (Wqkv): Linear(in_features=2048, out_features=6144, bias=True)\n",
              "        (out_proj): Linear(in_features=2048, out_features=2048, bias=True)\n",
              "        (inner_attn): SelfAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "        (inner_cross_attn): CrossAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (mlp): MLP(\n",
              "        (fc1): Linear(in_features=2048, out_features=8192, bias=True)\n",
              "        (fc2): Linear(in_features=8192, out_features=2048, bias=True)\n",
              "        (act): NewGELUActivation()\n",
              "      )\n",
              "    )\n",
              "    (14): ParallelBlock(\n",
              "      (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "      (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "      (mixer): MHA(\n",
              "        (rotary_emb): RotaryEmbedding()\n",
              "        (Wqkv): Linear(in_features=2048, out_features=6144, bias=True)\n",
              "        (out_proj): Linear(in_features=2048, out_features=2048, bias=True)\n",
              "        (inner_attn): SelfAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "        (inner_cross_attn): CrossAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (mlp): MLP(\n",
              "        (fc1): Linear(in_features=2048, out_features=8192, bias=True)\n",
              "        (fc2): Linear(in_features=8192, out_features=2048, bias=True)\n",
              "        (act): NewGELUActivation()\n",
              "      )\n",
              "    )\n",
              "    (15): ParallelBlock(\n",
              "      (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "      (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "      (mixer): MHA(\n",
              "        (rotary_emb): RotaryEmbedding()\n",
              "        (Wqkv): Linear(in_features=2048, out_features=6144, bias=True)\n",
              "        (out_proj): Linear(in_features=2048, out_features=2048, bias=True)\n",
              "        (inner_attn): SelfAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "        (inner_cross_attn): CrossAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (mlp): MLP(\n",
              "        (fc1): Linear(in_features=2048, out_features=8192, bias=True)\n",
              "        (fc2): Linear(in_features=8192, out_features=2048, bias=True)\n",
              "        (act): NewGELUActivation()\n",
              "      )\n",
              "    )\n",
              "    (16): ParallelBlock(\n",
              "      (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "      (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "      (mixer): MHA(\n",
              "        (rotary_emb): RotaryEmbedding()\n",
              "        (Wqkv): Linear(in_features=2048, out_features=6144, bias=True)\n",
              "        (out_proj): Linear(in_features=2048, out_features=2048, bias=True)\n",
              "        (inner_attn): SelfAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "        (inner_cross_attn): CrossAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (mlp): MLP(\n",
              "        (fc1): Linear(in_features=2048, out_features=8192, bias=True)\n",
              "        (fc2): Linear(in_features=8192, out_features=2048, bias=True)\n",
              "        (act): NewGELUActivation()\n",
              "      )\n",
              "    )\n",
              "    (17): ParallelBlock(\n",
              "      (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "      (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "      (mixer): MHA(\n",
              "        (rotary_emb): RotaryEmbedding()\n",
              "        (Wqkv): Linear(in_features=2048, out_features=6144, bias=True)\n",
              "        (out_proj): Linear(in_features=2048, out_features=2048, bias=True)\n",
              "        (inner_attn): SelfAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "        (inner_cross_attn): CrossAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (mlp): MLP(\n",
              "        (fc1): Linear(in_features=2048, out_features=8192, bias=True)\n",
              "        (fc2): Linear(in_features=8192, out_features=2048, bias=True)\n",
              "        (act): NewGELUActivation()\n",
              "      )\n",
              "    )\n",
              "    (18): ParallelBlock(\n",
              "      (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "      (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "      (mixer): MHA(\n",
              "        (rotary_emb): RotaryEmbedding()\n",
              "        (Wqkv): Linear(in_features=2048, out_features=6144, bias=True)\n",
              "        (out_proj): Linear(in_features=2048, out_features=2048, bias=True)\n",
              "        (inner_attn): SelfAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "        (inner_cross_attn): CrossAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (mlp): MLP(\n",
              "        (fc1): Linear(in_features=2048, out_features=8192, bias=True)\n",
              "        (fc2): Linear(in_features=8192, out_features=2048, bias=True)\n",
              "        (act): NewGELUActivation()\n",
              "      )\n",
              "    )\n",
              "    (19): ParallelBlock(\n",
              "      (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "      (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "      (mixer): MHA(\n",
              "        (rotary_emb): RotaryEmbedding()\n",
              "        (Wqkv): Linear(in_features=2048, out_features=6144, bias=True)\n",
              "        (out_proj): Linear(in_features=2048, out_features=2048, bias=True)\n",
              "        (inner_attn): SelfAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "        (inner_cross_attn): CrossAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (mlp): MLP(\n",
              "        (fc1): Linear(in_features=2048, out_features=8192, bias=True)\n",
              "        (fc2): Linear(in_features=8192, out_features=2048, bias=True)\n",
              "        (act): NewGELUActivation()\n",
              "      )\n",
              "    )\n",
              "    (20): ParallelBlock(\n",
              "      (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "      (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "      (mixer): MHA(\n",
              "        (rotary_emb): RotaryEmbedding()\n",
              "        (Wqkv): Linear(in_features=2048, out_features=6144, bias=True)\n",
              "        (out_proj): Linear(in_features=2048, out_features=2048, bias=True)\n",
              "        (inner_attn): SelfAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "        (inner_cross_attn): CrossAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (mlp): MLP(\n",
              "        (fc1): Linear(in_features=2048, out_features=8192, bias=True)\n",
              "        (fc2): Linear(in_features=8192, out_features=2048, bias=True)\n",
              "        (act): NewGELUActivation()\n",
              "      )\n",
              "    )\n",
              "    (21): ParallelBlock(\n",
              "      (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "      (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "      (mixer): MHA(\n",
              "        (rotary_emb): RotaryEmbedding()\n",
              "        (Wqkv): Linear(in_features=2048, out_features=6144, bias=True)\n",
              "        (out_proj): Linear(in_features=2048, out_features=2048, bias=True)\n",
              "        (inner_attn): SelfAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "        (inner_cross_attn): CrossAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (mlp): MLP(\n",
              "        (fc1): Linear(in_features=2048, out_features=8192, bias=True)\n",
              "        (fc2): Linear(in_features=8192, out_features=2048, bias=True)\n",
              "        (act): NewGELUActivation()\n",
              "      )\n",
              "    )\n",
              "    (22): ParallelBlock(\n",
              "      (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "      (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "      (mixer): MHA(\n",
              "        (rotary_emb): RotaryEmbedding()\n",
              "        (Wqkv): Linear(in_features=2048, out_features=6144, bias=True)\n",
              "        (out_proj): Linear(in_features=2048, out_features=2048, bias=True)\n",
              "        (inner_attn): SelfAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "        (inner_cross_attn): CrossAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (mlp): MLP(\n",
              "        (fc1): Linear(in_features=2048, out_features=8192, bias=True)\n",
              "        (fc2): Linear(in_features=8192, out_features=2048, bias=True)\n",
              "        (act): NewGELUActivation()\n",
              "      )\n",
              "    )\n",
              "    (23): ParallelBlock(\n",
              "      (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "      (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "      (mixer): MHA(\n",
              "        (rotary_emb): RotaryEmbedding()\n",
              "        (Wqkv): Linear(in_features=2048, out_features=6144, bias=True)\n",
              "        (out_proj): Linear(in_features=2048, out_features=2048, bias=True)\n",
              "        (inner_attn): SelfAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "        (inner_cross_attn): CrossAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (mlp): MLP(\n",
              "        (fc1): Linear(in_features=2048, out_features=8192, bias=True)\n",
              "        (fc2): Linear(in_features=8192, out_features=2048, bias=True)\n",
              "        (act): NewGELUActivation()\n",
              "      )\n",
              "    )\n",
              "    (24): ParallelBlock(\n",
              "      (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "      (resid_dropout): Dropout(p=0.0, inplace=False)\n",
              "      (mixer): MHA(\n",
              "        (rotary_emb): RotaryEmbedding()\n",
              "        (Wqkv): Linear(in_features=2048, out_features=6144, bias=True)\n",
              "        (out_proj): Linear(in_features=2048, out_features=2048, bias=True)\n",
              "        (inner_attn): SelfAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "        (inner_cross_attn): CrossAttention(\n",
              "          (drop): Dropout(p=0.0, inplace=False)\n",
              "        )\n",
              "      )\n",
              "      (mlp): MLP(\n",
              "        (fc1): Linear(in_features=2048, out_features=8192, bias=True)\n",
              "        (fc2): Linear(in_features=8192, out_features=2048, bias=True)\n",
              "        (act): NewGELUActivation()\n",
              "      )\n",
              "    )\n",
              "    (25): CausalLMHead(\n",
              "      (ln): LayerNorm((2048,), eps=1e-05, elementwise_affine=True)\n",
              "      (linear): Linear(in_features=2048, out_features=51200, bias=True)\n",
              "    )\n",
              "  )\n",
              "  (loss): CausalLMLoss(\n",
              "    (loss_fct): CrossEntropyLoss()\n",
              "  )\n",
              ")"
            ]
          },
          "metadata": {},
          "execution_count": 1
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import torch\n",
        "from transformers import AutoModelForCausalLM, AutoTokenizer\n",
        "\n",
        "model = AutoModelForCausalLM.from_pretrained(\"ashishpatel26/phi-1_5-finetuned-dialogstudio\", trust_remote_code=True, torch_dtype=torch.float32)\n",
        "tokenizer = AutoTokenizer.from_pretrained(\"microsoft/phi-1_5\", trust_remote_code=True)\n",
        "inputs = tokenizer(f'''{dataset[\"test\"]['text'][0]}''', return_tensors=\"pt\", return_attention_mask=False)\n",
        "\n",
        "outputs = model.generate(**inputs, max_length=512)\n",
        "text = tokenizer.batch_decode(outputs)[0]\n",
        "print(text)"
      ],
      "metadata": {
        "id": "vpbzxK0zhHk8"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# dataset[\"test\"]['text'][0]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 139
        },
        "id": "oU9augJbhm44",
        "outputId": "f85452c7-96a7-47e0-d3e8-52a7b12573aa"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'### Instruction: Below is a conversation between a human and an AI agent. Write a summary of the conversation.\\n\\n### Input:\\nuser: looking to change my flight Friday, Oct 27. GRMSKV to DL4728 from SLC to ORD. Is that an option and what is the cost? Jess\\nagent: The difference in fare is $185.30. This would include all airport taxes and fees. The ticket is non-refundable changeable with a fee, *ALS and may result in additional fare collection for changes when making a future changes. *ALS\\nuser: I had a first class seat purchased for the original flight, would that be the same with this flight to Chicago?\\nagent: Hello, Jess. That is the fare difference. You will have to call us at 1 800 221 1212 to make any changes. It is in First class. *TAY\\nuser: thx\\nagent: Our pleasure. *ALS\\nuser: Do I have to call or is there a means to do this online?\\nagent: You can call or you can login to your trip on our website to make changes. *TJE\\n\\n### Response:\\nCustomer is looking to change the flight on Friday Oct 27 is that an option and asking about cost. Agent replying that there is an difference in fare and this would include all airport taxes and fees and ticket is non refundable changeable with a fee.'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pfxoP-IvnheQ"
      },
      "source": [
        "## References\n",
        "\n",
        "- https://huggingface.co/datasets/Salesforce/dialogstudio\n",
        "- https://huggingface.co/meta-llama/Llama-2-7b-hf"
      ]
    }
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