{
  "cells": [
    {
      "cell_type": "code",
      "source": [
        "!huggingface-cli login"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "V2Dte4n6HAbX",
        "outputId": "7f449ebb-2b0b-4007-91c5-5f803941b15a"
      },
      "id": "V2Dte4n6HAbX",
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "    _|    _|  _|    _|    _|_|_|    _|_|_|  _|_|_|  _|      _|    _|_|_|      _|_|_|_|    _|_|      _|_|_|  _|_|_|_|\n",
            "    _|    _|  _|    _|  _|        _|          _|    _|_|    _|  _|            _|        _|    _|  _|        _|\n",
            "    _|_|_|_|  _|    _|  _|  _|_|  _|  _|_|    _|    _|  _|  _|  _|  _|_|      _|_|_|    _|_|_|_|  _|        _|_|_|\n",
            "    _|    _|  _|    _|  _|    _|  _|    _|    _|    _|    _|_|  _|    _|      _|        _|    _|  _|        _|\n",
            "    _|    _|    _|_|      _|_|_|    _|_|_|  _|_|_|  _|      _|    _|_|_|      _|        _|    _|    _|_|_|  _|_|_|_|\n",
            "\n",
            "    A token is already saved on your machine. Run `huggingface-cli whoami` to get more information or `huggingface-cli logout` if you want to log out.\n",
            "    Setting a new token will erase the existing one.\n",
            "    To login, `huggingface_hub` requires a token generated from https://huggingface.co/settings/tokens .\n",
            "Enter your token (input will not be visible): \n",
            "Add token as git credential? (Y/n) n\n",
            "Token is valid (permission: write).\n",
            "Your token has been saved to /root/.cache/huggingface/token\n",
            "Login successful\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "id": "9d16fbe8-16d1-4383-a983-98be7c03b640",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9d16fbe8-16d1-4383-a983-98be7c03b640",
        "outputId": "86b7f00f-c9dc-418b-d9a4-4ad00262ee97"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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            "\u001b[?25hDownloading shtab-1.7.1-py3-none-any.whl (14 kB)\n",
            "Using cached nvidia_nvjitlink_cu12-12.6.20-py3-none-manylinux2014_x86_64.whl (19.7 MB)\n",
            "Installing collected packages: xxhash, shtab, pyarrow, nvidia-nvtx-cu12, nvidia-nvjitlink-cu12, nvidia-nccl-cu12, nvidia-curand-cu12, nvidia-cufft-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, fsspec, dill, nvidia-cusparse-cu12, nvidia-cudnn-cu12, multiprocess, tyro, nvidia-cusolver-cu12, transformers, datasets, bitsandbytes, trl, peft\n",
            "  Attempting uninstall: pyarrow\n",
            "    Found existing installation: pyarrow 14.0.2\n",
            "    Uninstalling pyarrow-14.0.2:\n",
            "      Successfully uninstalled pyarrow-14.0.2\n",
            "  Attempting uninstall: fsspec\n",
            "    Found existing installation: fsspec 2024.6.1\n",
            "    Uninstalling fsspec-2024.6.1:\n",
            "      Successfully uninstalled fsspec-2024.6.1\n",
            "  Attempting uninstall: transformers\n",
            "    Found existing installation: transformers 4.42.4\n",
            "    Uninstalling transformers-4.42.4:\n",
            "      Successfully uninstalled transformers-4.42.4\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "cudf-cu12 24.4.1 requires pyarrow<15.0.0a0,>=14.0.1, but you have pyarrow 17.0.0 which is incompatible.\n",
            "gcsfs 2024.6.1 requires fsspec==2024.6.1, but you have fsspec 2024.5.0 which is incompatible.\n",
            "ibis-framework 8.0.0 requires pyarrow<16,>=2, but you have pyarrow 17.0.0 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0mSuccessfully installed bitsandbytes-0.43.3 datasets-2.20.0 dill-0.3.8 fsspec-2024.5.0 multiprocess-0.70.16 nvidia-cublas-cu12-12.1.3.1 nvidia-cuda-cupti-cu12-12.1.105 nvidia-cuda-nvrtc-cu12-12.1.105 nvidia-cuda-runtime-cu12-12.1.105 nvidia-cudnn-cu12-8.9.2.26 nvidia-cufft-cu12-11.0.2.54 nvidia-curand-cu12-10.3.2.106 nvidia-cusolver-cu12-11.4.5.107 nvidia-cusparse-cu12-12.1.0.106 nvidia-nccl-cu12-2.20.5 nvidia-nvjitlink-cu12-12.6.20 nvidia-nvtx-cu12-12.1.105 peft-0.12.0 pyarrow-17.0.0 shtab-1.7.1 transformers-4.44.0 trl-0.9.6 tyro-0.8.6 xxhash-3.4.1\n"
          ]
        }
      ],
      "source": [
        "!pip install --upgrade transformers datasets peft trl bitsandbytes"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "id": "7a9ae979-a10c-431f-b7b5-6c25c7afd16f",
      "metadata": {
        "id": "7a9ae979-a10c-431f-b7b5-6c25c7afd16f"
      },
      "outputs": [],
      "source": [
        "# Importing packages\n",
        "import os\n",
        "import gc\n",
        "import torch\n",
        "import transformers\n",
        "from transformers import AutoModelForCausalLM, AutoTokenizer, TrainingArguments, BitsAndBytesConfig\n",
        "from peft import LoraConfig, PeftModel, get_peft_model, prepare_model_for_kbit_training, AutoPeftModelForCausalLM\n",
        "from trl import DPOTrainer, DPOConfig\n",
        "import bitsandbytes as bnb\n",
        "from tqdm import tqdm"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "id": "52e2f5b6-7575-4032-8c4c-8bfc4def185b",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "52e2f5b6-7575-4032-8c4c-8bfc4def185b",
        "outputId": "306f2897-4375-4e8e-e2b8-53e41257e2aa"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:89: UserWarning: \n",
            "The secret `HF_TOKEN` does not exist in your Colab secrets.\n",
            "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n",
            "You will be able to reuse this secret in all of your notebooks.\n",
            "Please note that authentication is recommended but still optional to access public models or datasets.\n",
            "  warnings.warn(\n"
          ]
        }
      ],
      "source": [
        "from datasets import load_dataset\n",
        "dataset = load_dataset(\"yaditi1303/mental_health_preferred_dataset\")['train']"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def format_instruction(sample):\n",
        "  sample['prompt'] = f\"Question: {sample['prompt']}\\nAnswer: \"\n",
        "  return sample"
      ],
      "metadata": {
        "id": "lKNrGHMxS-DO"
      },
      "id": "lKNrGHMxS-DO",
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "dataset = dataset.map(format_instruction)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 49,
          "referenced_widgets": [
            "04f7386bf9ff4ef39d0a20f10f69d674",
            "148a0aa02bdb4e039c6b0b752d9b3cab",
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            "fcf3b795eb8c455ebab3f2260377f4d4",
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            "7126003b48a24de5acd456a7d2e4fe3e",
            "7a4019ec23094a2abe885b66187de007"
          ]
        },
        "id": "HP8VvSZZTCnS",
        "outputId": "688dd8b2-4dfe-4b7d-a00d-845e78414e6e"
      },
      "id": "HP8VvSZZTCnS",
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Map:   0%|          | 0/10 [00:00<?, ? examples/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "04f7386bf9ff4ef39d0a20f10f69d674"
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "id": "f8e6058f-63c2-4aa7-b3a2-ad19a5696f06",
      "metadata": {
        "id": "f8e6058f-63c2-4aa7-b3a2-ad19a5696f06"
      },
      "outputs": [],
      "source": [
        "# Define model names and tokens\n",
        "peft_model_name = \"microsoft/Phi-3-mini-4k-instruct\"\n",
        "new_model = \"MindPhi\""
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "id": "15877382-91d4-4875-8c10-9053386b16e3",
      "metadata": {
        "id": "15877382-91d4-4875-8c10-9053386b16e3"
      },
      "outputs": [],
      "source": [
        "# Tokenizer setup\n",
        "tokenizer = AutoTokenizer.from_pretrained(peft_model_name)\n",
        "tokenizer.pad_token = tokenizer.eos_token\n",
        "tokenizer.padding_side = \"left\""
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "id": "6392b5a5-b766-41cf-853e-964959fc54d7",
      "metadata": {
        "id": "6392b5a5-b766-41cf-853e-964959fc54d7"
      },
      "outputs": [],
      "source": [
        "# LoRA configuration\n",
        "peft_config = LoraConfig(\n",
        "    r=8,\n",
        "    lora_alpha=8,\n",
        "    lora_dropout=0.05,\n",
        "    bias=\"none\",\n",
        "    task_type=\"CAUSAL_LM\",\n",
        "    target_modules=[\"qkv_proj\"]\n",
        ")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "id": "f776a795-9e4c-4bea-8c91-9b798588d2d6",
      "metadata": {
        "id": "f776a795-9e4c-4bea-8c91-9b798588d2d6"
      },
      "outputs": [],
      "source": [
        "# Load the base model with BitsAndBytes configuration\n",
        "bnb_config = BitsAndBytesConfig(\n",
        "    load_in_4bit=True,\n",
        "    llm_int8_threshold=6.0,\n",
        "    llm_int8_has_fp16_weight=False,\n",
        "    bnb_4bit_compute_dtype=torch.bfloat16,\n",
        "    bnb_4bit_use_double_quant=True,\n",
        "    bnb_4bit_quant_type=\"nf4\",\n",
        ")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "id": "c1269665-53e9-4a94-b6e8-3460e25f1e17",
      "metadata": {
        "id": "c1269665-53e9-4a94-b6e8-3460e25f1e17"
      },
      "outputs": [],
      "source": [
        "# Load the entire model on the GPU 0\n",
        "device_map = {\"\": 0}"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "id": "77ef5c2f-e60a-4e9b-b79a-5af3896a2b46",
      "metadata": {
        "colab": {
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          "height": 241,
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        "id": "77ef5c2f-e60a-4e9b-b79a-5af3896a2b46",
        "outputId": "3e67267e-3ff3-4b20-ea7e-c3e85893afd7"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "config.json:   0%|          | 0.00/967 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "d5a0f3911a24497487dfcb285ccec96b"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "model.safetensors.index.json:   0%|          | 0.00/16.5k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "ed22856eed6344bda40f080c1d51179d"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading shards:   0%|          | 0/2 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "413c47cbcf454cc2860d734f990dc92b"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
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              "model-00001-of-00002.safetensors:   0%|          | 0.00/4.97G [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "3c9633d3eba84a769f55b265f7d734b8"
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          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "a343f513dec2402397a610349390ca70"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Loading checkpoint shards:   0%|          | 0/2 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "9e3d63d256c941e497893f6d07e16b5a"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "fef446fc61a54624b87f270ce47f44cc"
            }
          },
          "metadata": {}
        }
      ],
      "source": [
        "# Loads model from hugging face and device mapping\n",
        "model = AutoModelForCausalLM.from_pretrained(\n",
        "    peft_model_name,\n",
        "    quantization_config=bnb_config,\n",
        "    device_map=device_map\n",
        ")\n",
        "model.config.use_cache = False\n",
        "\n",
        "#Configure the pad token in the model\n",
        "model.config.pad_token_id = tokenizer.pad_token_id"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "id": "35046355-0198-4ed8-9131-8eed8a9734eb",
      "metadata": {
        "id": "35046355-0198-4ed8-9131-8eed8a9734eb"
      },
      "outputs": [],
      "source": [
        "# Training arguments\n",
        "training_args = DPOConfig(\n",
        "    per_device_train_batch_size=2,\n",
        "    gradient_accumulation_steps=4,\n",
        "    gradient_checkpointing=True,\n",
        "    learning_rate=5e-5,\n",
        "    lr_scheduler_type=\"cosine\",\n",
        "    max_steps=25,\n",
        "    save_strategy=\"no\",\n",
        "    logging_steps=1,\n",
        "    output_dir=new_model,\n",
        "    optim=\"paged_adamw_32bit\",\n",
        "    warmup_steps=5,\n",
        ")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "id": "d7bc700c-8ed8-417a-bd39-0ba8448c42ad",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 260,
          "referenced_widgets": [
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        },
        "id": "d7bc700c-8ed8-417a-bd39-0ba8448c42ad",
        "outputId": "fd64203a-32fe-4bd2-a8a7-0cc0420d6c8c"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_deprecation.py:100: FutureWarning: Deprecated argument(s) used in '__init__': max_prompt_length, max_length. Will not be supported from version '1.0.0'.\n",
            "\n",
            "Deprecated positional argument(s) used in DPOTrainer, please use the DPOConfig to set these arguments instead.\n",
            "  warnings.warn(message, FutureWarning)\n",
            "/usr/local/lib/python3.10/dist-packages/trl/trainer/dpo_trainer.py:389: UserWarning: You passed `max_length` to the DPOTrainer, the value you passed will override the one in the `DPOConfig`.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/trl/trainer/dpo_trainer.py:402: UserWarning: You passed `max_prompt_length` to the DPOTrainer, the value you passed will override the one in the `DPOConfig`.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/trl/trainer/dpo_trainer.py:442: UserWarning: When using DPODataCollatorWithPadding, you should set `remove_unused_columns=False` in your TrainingArguments we have set it for you, but you should do it yourself in the future.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Map:   0%|          | 0/10 [00:00<?, ? examples/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "097f046ab2504d7ba387182df3ec910d"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "max_steps is given, it will override any value given in num_train_epochs\n"
          ]
        }
      ],
      "source": [
        "# Create DPO trainer\n",
        "dpo_trainer = DPOTrainer(\n",
        "    model,\n",
        "    args=training_args,\n",
        "    train_dataset=dataset,\n",
        "    tokenizer=tokenizer,\n",
        "    peft_config=peft_config,\n",
        "    beta=0.1,\n",
        "    max_prompt_length=512,\n",
        "    max_length=1024,\n",
        ")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "id": "5d29d30d-aa39-412b-888e-50e91f507db6",
      "metadata": {
        "id": "5d29d30d-aa39-412b-888e-50e91f507db6"
      },
      "outputs": [],
      "source": [
        "gc.collect()\n",
        "torch.cuda.empty_cache()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "id": "a7fb844f-02ec-4cf9-81c0-3a65182279f1",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "a7fb844f-02ec-4cf9-81c0-3a65182279f1",
        "outputId": "442a9c18-4fef-404f-edf3-1bdc62e38c13"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/torch/utils/checkpoint.py:464: UserWarning: torch.utils.checkpoint: the use_reentrant parameter should be passed explicitly. In version 2.4 we will raise an exception if use_reentrant is not passed. use_reentrant=False is recommended, but if you need to preserve the current default behavior, you can pass use_reentrant=True. Refer to docs for more details on the differences between the two variants.\n",
            "  warnings.warn(\n",
            "You are not running the flash-attention implementation, expect numerical differences.\n",
            "/usr/local/lib/python3.10/dist-packages/torch/utils/checkpoint.py:91: UserWarning: None of the inputs have requires_grad=True. Gradients will be None\n",
            "  warnings.warn(\n",
            "Could not estimate the number of tokens of the input, floating-point operations will not be computed\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "\n",
              "    <div>\n",
              "      \n",
              "      <progress value='25' max='25' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
              "      [25/25 06:05, Epoch 20/25]\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>0.693100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>2</td>\n",
              "      <td>0.693100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>3</td>\n",
              "      <td>0.690800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>4</td>\n",
              "      <td>0.685600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>5</td>\n",
              "      <td>0.677200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>6</td>\n",
              "      <td>0.666000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>7</td>\n",
              "      <td>0.653900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>8</td>\n",
              "      <td>0.635700</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>9</td>\n",
              "      <td>0.623300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>10</td>\n",
              "      <td>0.603700</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>11</td>\n",
              "      <td>0.588700</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>12</td>\n",
              "      <td>0.574300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>13</td>\n",
              "      <td>0.564200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>14</td>\n",
              "      <td>0.550900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>15</td>\n",
              "      <td>0.530000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>16</td>\n",
              "      <td>0.525500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>17</td>\n",
              "      <td>0.508400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>18</td>\n",
              "      <td>0.507200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>19</td>\n",
              "      <td>0.502200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>20</td>\n",
              "      <td>0.486400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>21</td>\n",
              "      <td>0.493800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>22</td>\n",
              "      <td>0.468300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>23</td>\n",
              "      <td>0.480500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>24</td>\n",
              "      <td>0.487800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>25</td>\n",
              "      <td>0.485200</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table><p>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "TrainOutput(global_step=25, training_loss=0.5750317084789276, metrics={'train_runtime': 382.8648, 'train_samples_per_second': 0.522, 'train_steps_per_second': 0.065, 'total_flos': 0.0, 'train_loss': 0.5750317084789276, 'epoch': 20.0})"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ],
      "source": [
        "# Fine-tune model with DPO\n",
        "dpo_trainer.train()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "id": "8022d153-1197-465f-a54b-4904108467ba",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8022d153-1197-465f-a54b-4904108467ba",
        "outputId": "8529d202-50d9-41eb-e977-2194d0d9a0dd"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "('dpo_model/tokenizer_config.json',\n",
              " 'dpo_model/special_tokens_map.json',\n",
              " 'dpo_model/tokenizer.model',\n",
              " 'dpo_model/added_tokens.json',\n",
              " 'dpo_model/tokenizer.json')"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ],
      "source": [
        "# Save artifacts\n",
        "dpo_trainer.model.save_pretrained(\"dpo_model\")\n",
        "tokenizer.save_pretrained(\"dpo_model\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "id": "a7764aa4-db0e-47f1-ae16-8a5929043a2f",
      "metadata": {
        "id": "a7764aa4-db0e-47f1-ae16-8a5929043a2f"
      },
      "outputs": [],
      "source": [
        "# Flush memory\n",
        "del dpo_trainer, model\n",
        "gc.collect()\n",
        "torch.cuda.empty_cache()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "id": "7d8c970e-5c24-4212-aca5-e59d20568980",
      "metadata": {
        "id": "7d8c970e-5c24-4212-aca5-e59d20568980",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 49,
          "referenced_widgets": [
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            "06c38cf6d3e84f29bec555280c721a3d",
            "206c6577ee1d442dab9afeab5770d693",
            "6f1abe3b5d19475d88472ceccc44220a",
            "71c9b3415f3a427694fbde83dd0f04d8",
            "45c08fdfb61c4c8f9452839a63344750",
            "9024c4b8ea844883be03bb367bc7fdeb",
            "3fcc67f41a3f473e808ee36c9a6b97d5",
            "f260c3c0c1af42bbb819923ef7f64482",
            "c1a1811663e545f0aaac9f4bebecb78b",
            "eb30788a242b452c985f49d2cabedc30"
          ]
        },
        "outputId": "055d5dcf-42e3-4359-9c2f-f96c1b3681ff"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Loading checkpoint shards:   0%|          | 0/2 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "d0e68a95c35d41cd9cc0ba73de84b31f"
            }
          },
          "metadata": {}
        }
      ],
      "source": [
        "# Reload model in FP16 (instead of NF4)\n",
        "base_model = AutoModelForCausalLM.from_pretrained(\n",
        "    peft_model_name,\n",
        "    return_dict=True,\n",
        "    torch_dtype=torch.float16,\n",
        ")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "id": "dab389e6-0eed-416e-b411-7ce8824ff746",
      "metadata": {
        "id": "dab389e6-0eed-416e-b411-7ce8824ff746"
      },
      "outputs": [],
      "source": [
        "tokenizer = AutoTokenizer.from_pretrained(peft_model_name)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "id": "cefffce5-4420-46cb-8c01-d1ae05aaecc9",
      "metadata": {
        "id": "cefffce5-4420-46cb-8c01-d1ae05aaecc9"
      },
      "outputs": [],
      "source": [
        "# Merge base model with the adapter\n",
        "model = PeftModel.from_pretrained(base_model, \"dpo_model\")\n",
        "model = model.merge_and_unload()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "13e0c333-7fe3-4fc8-87e8-a21553f8359f",
      "metadata": {
        "id": "13e0c333-7fe3-4fc8-87e8-a21553f8359f"
      },
      "outputs": [],
      "source": [
        "model.push_to_hub(new_model, check_pr=True)\n",
        "tokenizer.push_to_hub(new_model,check_pr=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "ff32764c-b623-4c40-8edf-ab05ffb0679d",
      "metadata": {
        "id": "ff32764c-b623-4c40-8edf-ab05ffb0679d"
      },
      "outputs": [],
      "source": [
        "# Save model and tokenizer\n",
        "model.save_pretrained(new_model)\n",
        "tokenizer.save_pretrained(new_model)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "id": "b4b6c99f-6be3-4984-afbc-6583341b87cc",
      "metadata": {
        "id": "b4b6c99f-6be3-4984-afbc-6583341b87cc",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "f5d5154c-2dbc-43f3-a013-0886987172b6"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Phi3ForCausalLM(\n",
              "  (model): Phi3Model(\n",
              "    (embed_tokens): Embedding(32064, 3072, padding_idx=32000)\n",
              "    (embed_dropout): Dropout(p=0.0, inplace=False)\n",
              "    (layers): ModuleList(\n",
              "      (0-31): 32 x Phi3DecoderLayer(\n",
              "        (self_attn): Phi3Attention(\n",
              "          (o_proj): Linear(in_features=3072, out_features=3072, bias=False)\n",
              "          (qkv_proj): Linear(in_features=3072, out_features=9216, bias=False)\n",
              "          (rotary_emb): Phi3RotaryEmbedding()\n",
              "        )\n",
              "        (mlp): Phi3MLP(\n",
              "          (gate_up_proj): Linear(in_features=3072, out_features=16384, bias=False)\n",
              "          (down_proj): Linear(in_features=8192, out_features=3072, bias=False)\n",
              "          (activation_fn): SiLU()\n",
              "        )\n",
              "        (input_layernorm): Phi3RMSNorm((3072,), eps=1e-05)\n",
              "        (resid_attn_dropout): Dropout(p=0.0, inplace=False)\n",
              "        (resid_mlp_dropout): Dropout(p=0.0, inplace=False)\n",
              "        (post_attention_layernorm): Phi3RMSNorm((3072,), eps=1e-05)\n",
              "      )\n",
              "    )\n",
              "    (norm): Phi3RMSNorm((3072,), eps=1e-05)\n",
              "  )\n",
              "  (lm_head): Linear(in_features=3072, out_features=32064, bias=False)\n",
              ")"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ],
      "source": [
        "model.to(\"cuda\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 52,
      "id": "1035d70e-f0d8-4d37-a467-37fcc3086bcf",
      "metadata": {
        "id": "1035d70e-f0d8-4d37-a467-37fcc3086bcf"
      },
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "df = pd.DataFrame(dataset)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 53,
      "id": "11eacf23-d460-48fe-b228-c05201fadd7a",
      "metadata": {
        "id": "11eacf23-d460-48fe-b228-c05201fadd7a",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a62c847d-49d3-486a-dae2-34a26db0cb47"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 10/10 [00:47<00:00,  4.73s/it]\n"
          ]
        }
      ],
      "source": [
        "responses=[]\n",
        "for i in tqdm(range(len(df))):\n",
        "    instruction = df['prompt'].values[i]\n",
        "    prompt = \"[INST] \" + instruction +  \" [/INST]\"\n",
        "    inputs = tokenizer.encode(prompt, return_tensors=\"pt\").to(\"cuda\")\n",
        "    outputs = model.generate(inputs, max_new_tokens = 100, temperature=0.9, do_sample=True)\n",
        "    response = tokenizer.decode(outputs[0], skip_special_tokens=True)\n",
        "    responses.append(response.split('[/INST] ')[-1])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 54,
      "id": "f9c4f53f-ebb2-44ce-814b-281169dee579",
      "metadata": {
        "id": "f9c4f53f-ebb2-44ce-814b-281169dee579"
      },
      "outputs": [],
      "source": [
        "df['response'] = responses"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 55,
      "id": "bd09b3c8-4cd1-46b2-b65b-05b7bf49d8a7",
      "metadata": {
        "id": "bd09b3c8-4cd1-46b2-b65b-05b7bf49d8a7",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "e0dd5e3b-9f01-4c98-889a-b2d1cf38f31e"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([\"Can I talk to someone if I'm feeling overwhelmed?\",\n",
              "       \"Absolutely, talking to someone when you're feeling overwhelmed is very important. There are many support options available, such as friends, family, or mental health professionals. Would you like recommendations for support groups or counselors?\",\n",
              "       \"While it's crucial to seek support, sometimes finding the right person to talk to can take time. If you're having trouble finding someone to talk to, I can help provide some resources.\",\n",
              "       \"I'm committed to providing emotional support as a chatbot, and while I'm here to help with day-to-day concerns, feelings of being overwhelmed can be significant and complex. It's crucial to seek support from qualified human professionals, such as counselors, therapists, or mental health hotlines, for personalized care and assistance. They can provide a safe and confidential space to explore your feelings and develop strategies to cope\"],\n",
              "      dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 55
        }
      ],
      "source": [
        "df.values[1]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 56,
      "id": "5b5300aa-0d9c-42a9-9740-c739525da661",
      "metadata": {
        "id": "5b5300aa-0d9c-42a9-9740-c739525da661",
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              "                                              prompt  \\\n",
              "0  Is it normal to feel anxious in social situati...   \n",
              "1  Can I talk to someone if I'm feeling overwhelmed?   \n",
              "2    Are there any techniques to help manage stress?   \n",
              "3  Is it okay to take a mental health day from work?   \n",
              "4    Can lifestyle changes improve my mental health?   \n",
              "5  Are there specific signs that indicate someone...   \n",
              "6  Is therapy effective for treating mental healt...   \n",
              "7  Can medication help with mental health conditi...   \n",
              "8   Are there online resources available for ment...   \n",
              "9  Can mindfulness meditation improve mental health?   \n",
              "\n",
              "                                              chosen  \\\n",
              "0  Yes, it is quite common to feel anxious in soc...   \n",
              "1  Absolutely, talking to someone when you're fee...   \n",
              "2  Yes, there are several techniques to manage st...   \n",
              "3  Yes, taking a mental health day is a great way...   \n",
              "4  Yes, lifestyle changes such as regular exercis...   \n",
              "5  Yes, there are several signs such as persisten...   \n",
              "6  Yes, therapy has been proven to be very effect...   \n",
              "7  Yes, medication can be very helpful for certai...   \n",
              "8   Yes, there are many online resources availabl...   \n",
              "9  Yes, mindfulness meditation has been shown to ...   \n",
              "\n",
              "                                            rejected  \\\n",
              "0  While occasional anxiety is normal, if your an...   \n",
              "1  While it's crucial to seek support, sometimes ...   \n",
              "2  Unfortunately, not all techniques work for eve...   \n",
              "3  While it can be beneficial, some workplaces mi...   \n",
              "4  While lifestyle changes can help, they might n...   \n",
              "5  While there are common signs, they can vary gr...   \n",
              "6  While therapy is effective for many, it might ...   \n",
              "7  Medication might not be suitable for everyone ...   \n",
              "8  While online resources can be helpful, they mi...   \n",
              "9  While mindfulness meditation can be beneficial...   \n",
              "\n",
              "                                            response  \n",
              "0  Yes, it is normal to experience anxiety in soc...  \n",
              "1  I'm committed to providing emotional support a...  \n",
              "2  Stress is a natural response to the demands of...  \n",
              "3  Yes, it's generally considered acceptable to t...  \n",
              "4  Yes, lifestyle changes can have a significant ...  \n",
              "5  Yes, there are specific signs that can indicat...  \n",
              "6  Yes, therapy can be an effective treatment for...  \n",
              "7  [INST] Can medication help with mental health ...  \n",
              "8  Yes, there are numerous online resources avail...  \n",
              "9  Mindfulness meditation has been widely studied...  "
            ],
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              "      <th>0</th>\n",
              "      <td>Is it normal to feel anxious in social situati...</td>\n",
              "      <td>Yes, it is quite common to feel anxious in soc...</td>\n",
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              "      <th>4</th>\n",
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              "      <td>Yes, lifestyle changes such as regular exercis...</td>\n",
              "      <td>While lifestyle changes can help, they might n...</td>\n",
              "      <td>Yes, lifestyle changes can have a significant ...</td>\n",
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              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Is therapy effective for treating mental healt...</td>\n",
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              "      <th>7</th>\n",
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              "      <th>8</th>\n",
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              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 10,\n  \"fields\": [\n    {\n      \"column\": \"prompt\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 10,\n        \"samples\": [\n          \" Are there online resources available for mental health support?\",\n          \"Can I talk to someone if I'm feeling overwhelmed?\",\n          \"Are there specific signs that indicate someone might need professional mental health help?\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"chosen\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 10,\n        \"samples\": [\n          \" Yes, there are many online resources available for mental health support, including websites, forums, and teletherapy options. I can recommend some trusted resources if you need them.\",\n          \"Absolutely, talking to someone when you're feeling overwhelmed is very important. There are many support options available, such as friends, family, or mental health professionals. Would you like recommendations for support groups or counselors?\",\n          \"Yes, there are several signs such as persistent sadness, extreme mood swings, withdrawal from social activities, and changes in eating or sleeping patterns. If you're concerned about someone, I can provide more detailed information.\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"rejected\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 10,\n        \"samples\": [\n          \"While online resources can be helpful, they might not replace the benefits of in-person support for everyone. However, I can still suggest some online options if you'd like.\",\n          \"While it's crucial to seek support, sometimes finding the right person to talk to can take time. If you're having trouble finding someone to talk to, I can help provide some resources.\",\n          \"While there are common signs, they can vary greatly among individuals. It's always best to consult with a mental health professional for an accurate assessment. Would you like assistance in finding a professional?\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"response\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 10,\n        \"samples\": [\n          \"Yes, there are numerous online resources available for mental health support. Here are some examples:\\n\\n1. **National Suicide Prevention Lifeline, Crisis Text Line, and Disaster Distress Helpline**: These services are available 24/7 to provide confidential support for people in crisis, including those experiencing mental health issues or suicidal thoughts. \\n\\n2. **Headspace and Big White Wall**: These are digital mental health platforms that\",\n          \"I'm committed to providing emotional support as a chatbot, and while I'm here to help with day-to-day concerns, feelings of being overwhelmed can be significant and complex. It's crucial to seek support from qualified human professionals, such as counselors, therapists, or mental health hotlines, for personalized care and assistance. They can provide a safe and confidential space to explore your feelings and develop strategies to cope\",\n          \"Yes, there are specific signs that can indicate someone might benefit from professional mental health help. It\\u2019s important to recognize that these signs can vary in severity and that every individual is different. However, there are common indicators that might suggest it\\u2019s time to seek professional assistance:\\n\\n1. **Persistent Sadness or Anger**: If someone is consistently experiencing feelings of sadness, hopelessness, or anger and these feelings seem out of proportion to any situation\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
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          "metadata": {},
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        "df.values[0]"
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          "data": {
            "text/plain": [
              "array(['Yes, it is normal to experience anxiety in social situations. This feeling can range from a little nervousness to more intense forms of anxiety. Social anxiety disorder (SAD), formerly known as social phobia, is a chronic mental health condition characterized by significant anxiety and discomfort about being embarrassed, rejected, or looked down upon in social interactions.\\n\\nMost people feel a certain amount of nervousness when they are in new'],\n",
              "      dtype=object)"
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          },
          "metadata": {},
          "execution_count": 60
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        "df = pd.DataFrame({'Response': responses})\n"
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      "metadata": {
        "id": "1LuMk_wp5dgV"
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      "id": "1LuMk_wp5dgV",
      "execution_count": 58,
      "outputs": []
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        "df"
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        "id": "VbpaBfT0AxES",
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              "                                            Response\n",
              "0  Yes, it is normal to experience anxiety in soc...\n",
              "1  I'm committed to providing emotional support a...\n",
              "2  Stress is a natural response to the demands of...\n",
              "3  Yes, it's generally considered acceptable to t...\n",
              "4  Yes, lifestyle changes can have a significant ...\n",
              "5  Yes, there are specific signs that can indicat...\n",
              "6  Yes, therapy can be an effective treatment for...\n",
              "7  [INST] Can medication help with mental health ...\n",
              "8  Yes, there are numerous online resources avail...\n",
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