{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "execution": {
     "iopub.execute_input": "2025-06-20T05:52:07.947918Z",
     "iopub.status.busy": "2025-06-20T05:52:07.947486Z",
     "iopub.status.idle": "2025-06-20T05:52:08.670792Z",
     "shell.execute_reply": "2025-06-20T05:52:08.670091Z",
     "shell.execute_reply.started": "2025-06-20T05:52:07.947894Z"
    },
    "executionInfo": {
     "elapsed": 1054,
     "status": "ok",
     "timestamp": 1750131954055,
     "user": {
      "displayName": "Da T",
      "userId": "15660101803040065430"
     },
     "user_tz": -420
    },
    "id": "d0EjhGD8FoSZ",
    "outputId": "50957539-31a3-4e6a-d268-216bb8e6d685",
    "trusted": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The token has not been saved to the git credentials helper. Pass `add_to_git_credential=True` in this function directly or `--add-to-git-credential` if using via `huggingface-cli` if you want to set the git credential as well.\n",
      "Token is valid (permission: read).\n",
      "The token `read-only` has been saved to /root/.cache/huggingface/stored_tokens\n",
      "Your token has been saved to /root/.cache/huggingface/token\n",
      "Login successful.\n",
      "The current active token is: `read-only`\n"
     ]
    }
   ],
   "source": [
    "from huggingface_hub import notebook_login\n",
    "notebook_login()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "execution": {
     "iopub.execute_input": "2025-06-20T05:52:09.038485Z",
     "iopub.status.busy": "2025-06-20T05:52:09.037853Z",
     "iopub.status.idle": "2025-06-20T05:52:25.530624Z",
     "shell.execute_reply": "2025-06-20T05:52:25.529703Z",
     "shell.execute_reply.started": "2025-06-20T05:52:09.038455Z"
    },
    "executionInfo": {
     "elapsed": 7264,
     "status": "ok",
     "timestamp": 1750131961771,
     "user": {
      "displayName": "Da T",
      "userId": "15660101803040065430"
     },
     "user_tz": -420
    },
    "id": "x9rP-YzHfS0Q",
    "outputId": "04fd4861-ebd0-4678-ade4-2336d3c9794e",
    "trusted": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/content\n",
      "Cloning into 'diffusers'...\n",
      "remote: Enumerating objects: 96198, done.\u001b[K\n",
      "remote: Counting objects: 100% (1030/1030), done.\u001b[K\n",
      "remote: Compressing objects: 100% (404/404), done.\u001b[K\n",
      "remote: Total 96198 (delta 854), reused 636 (delta 610), pack-reused 95168 (from 4)\u001b[K\n",
      "Receiving objects: 100% (96198/96198), 72.94 MiB | 31.60 MiB/s, done.\n",
      "Resolving deltas: 100% (70583/70583), done.\n",
      "/content/diffusers\n",
      "Obtaining file:///content/diffusers\n",
      "  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
      "  Checking if build backend supports build_editable ... \u001b[?25l\u001b[?25hdone\n",
      "  Getting requirements to build editable ... \u001b[?25l\u001b[?25hdone\n",
      "  Preparing editable metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
      "Requirement already satisfied: importlib_metadata in /usr/local/lib/python3.11/dist-packages (from diffusers==0.34.0.dev0) (8.7.0)\n",
      "Requirement already satisfied: filelock in /usr/local/lib/python3.11/dist-packages (from diffusers==0.34.0.dev0) (3.18.0)\n",
      "Requirement already satisfied: huggingface-hub>=0.27.0 in /usr/local/lib/python3.11/dist-packages (from diffusers==0.34.0.dev0) (0.31.1)\n",
      "Requirement already satisfied: numpy in /usr/local/lib/python3.11/dist-packages (from diffusers==0.34.0.dev0) (1.26.4)\n",
      "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.11/dist-packages (from diffusers==0.34.0.dev0) (2024.11.6)\n",
      "Requirement already satisfied: requests in /usr/local/lib/python3.11/dist-packages (from diffusers==0.34.0.dev0) (2.32.3)\n",
      "Requirement already satisfied: safetensors>=0.3.1 in /usr/local/lib/python3.11/dist-packages (from diffusers==0.34.0.dev0) (0.5.3)\n",
      "Requirement already satisfied: Pillow in /usr/local/lib/python3.11/dist-packages (from diffusers==0.34.0.dev0) (11.1.0)\n",
      "Requirement already satisfied: fsspec>=2023.5.0 in /usr/local/lib/python3.11/dist-packages (from huggingface-hub>=0.27.0->diffusers==0.34.0.dev0) (2025.3.2)\n",
      "Requirement already satisfied: packaging>=20.9 in /usr/local/lib/python3.11/dist-packages (from huggingface-hub>=0.27.0->diffusers==0.34.0.dev0) (25.0)\n",
      "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.11/dist-packages (from huggingface-hub>=0.27.0->diffusers==0.34.0.dev0) (6.0.2)\n",
      "Requirement already satisfied: tqdm>=4.42.1 in /usr/local/lib/python3.11/dist-packages (from huggingface-hub>=0.27.0->diffusers==0.34.0.dev0) (4.67.1)\n",
      "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.11/dist-packages (from huggingface-hub>=0.27.0->diffusers==0.34.0.dev0) (4.13.2)\n",
      "Requirement already satisfied: hf-xet<2.0.0,>=1.1.0 in /usr/local/lib/python3.11/dist-packages (from huggingface-hub>=0.27.0->diffusers==0.34.0.dev0) (1.1.0)\n",
      "Requirement already satisfied: zipp>=3.20 in /usr/local/lib/python3.11/dist-packages (from importlib_metadata->diffusers==0.34.0.dev0) (3.21.0)\n",
      "Requirement already satisfied: mkl_fft in /usr/local/lib/python3.11/dist-packages (from numpy->diffusers==0.34.0.dev0) (1.3.8)\n",
      "Requirement already satisfied: mkl_random in /usr/local/lib/python3.11/dist-packages (from numpy->diffusers==0.34.0.dev0) (1.2.4)\n",
      "Requirement already satisfied: mkl_umath in /usr/local/lib/python3.11/dist-packages (from numpy->diffusers==0.34.0.dev0) (0.1.1)\n",
      "Requirement already satisfied: mkl in /usr/local/lib/python3.11/dist-packages (from numpy->diffusers==0.34.0.dev0) (2025.1.0)\n",
      "Requirement already satisfied: tbb4py in /usr/local/lib/python3.11/dist-packages (from numpy->diffusers==0.34.0.dev0) (2022.1.0)\n",
      "Requirement already satisfied: mkl-service in /usr/local/lib/python3.11/dist-packages (from numpy->diffusers==0.34.0.dev0) (2.4.1)\n",
      "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.11/dist-packages (from requests->diffusers==0.34.0.dev0) (3.4.2)\n",
      "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.11/dist-packages (from requests->diffusers==0.34.0.dev0) (3.10)\n",
      "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.11/dist-packages (from requests->diffusers==0.34.0.dev0) (2.4.0)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.11/dist-packages (from requests->diffusers==0.34.0.dev0) (2025.4.26)\n",
      "Requirement already satisfied: intel-openmp<2026,>=2024 in /usr/local/lib/python3.11/dist-packages (from mkl->numpy->diffusers==0.34.0.dev0) (2024.2.0)\n",
      "Requirement already satisfied: tbb==2022.* in /usr/local/lib/python3.11/dist-packages (from mkl->numpy->diffusers==0.34.0.dev0) (2022.1.0)\n",
      "Requirement already satisfied: tcmlib==1.* in /usr/local/lib/python3.11/dist-packages (from tbb==2022.*->mkl->numpy->diffusers==0.34.0.dev0) (1.3.0)\n",
      "Requirement already satisfied: intel-cmplr-lib-rt in /usr/local/lib/python3.11/dist-packages (from mkl_umath->numpy->diffusers==0.34.0.dev0) (2024.2.0)\n",
      "Requirement already satisfied: intel-cmplr-lib-ur==2024.2.0 in /usr/local/lib/python3.11/dist-packages (from intel-openmp<2026,>=2024->mkl->numpy->diffusers==0.34.0.dev0) (2024.2.0)\n",
      "Building wheels for collected packages: diffusers\n",
      "  Building editable for diffusers (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
      "  Created wheel for diffusers: filename=diffusers-0.34.0.dev0-0.editable-py3-none-any.whl size=11367 sha256=016c6e49433c5b6fb541413d9c1cf8ab149167dab06e34d3d0b2a7470abbf281\n",
      "  Stored in directory: /tmp/pip-ephem-wheel-cache-giq3v8s6/wheels/30/15/ca/ab6e88c89d6ba7047b3f155894c6c346e7cf06067fd132ae62\n",
      "Successfully built diffusers\n",
      "Installing collected packages: diffusers\n",
      "  Attempting uninstall: diffusers\n",
      "    Found existing installation: diffusers 0.32.2\n",
      "    Uninstalling diffusers-0.32.2:\n",
      "      Successfully uninstalled diffusers-0.32.2\n",
      "Successfully installed diffusers-0.34.0.dev0\n",
      "/content\n"
     ]
    }
   ],
   "source": [
    "%cd /content\n",
    "!git clone https://github.com/huggingface/diffusers\n",
    "%cd diffusers\n",
    "!pip install -e .\n",
    "%cd .."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "execution": {
     "iopub.execute_input": "2025-06-20T05:52:25.532533Z",
     "iopub.status.busy": "2025-06-20T05:52:25.532191Z",
     "iopub.status.idle": "2025-06-20T05:53:36.929477Z",
     "shell.execute_reply": "2025-06-20T05:53:36.928515Z",
     "shell.execute_reply.started": "2025-06-20T05:52:25.532496Z"
    },
    "executionInfo": {
     "elapsed": 86476,
     "status": "ok",
     "timestamp": 1750132068564,
     "user": {
      "displayName": "Da T",
      "userId": "15660101803040065430"
     },
     "user_tz": -420
    },
    "id": "jVFhIC8egN40",
    "outputId": "36d7482a-54ff-43e4-b050-0a50b7ba9396",
    "trusted": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m410.8/410.8 kB\u001b[0m \u001b[31m7.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0ma \u001b[36m0:00:01\u001b[0m\n",
      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m193.6/193.6 kB\u001b[0m \u001b[31m12.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m363.4/363.4 MB\u001b[0m \u001b[31m4.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m0:00:01\u001b[0m00:01\u001b[0m\n",
      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m664.8/664.8 MB\u001b[0m \u001b[31m2.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m0:00:01\u001b[0m00:01\u001b[0m\n",
      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m211.5/211.5 MB\u001b[0m \u001b[31m6.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m0:00:01\u001b[0m00:01\u001b[0m\n",
      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m56.3/56.3 MB\u001b[0m \u001b[31m30.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m:00:01\u001b[0m00:01\u001b[0m\n",
      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m127.9/127.9 MB\u001b[0m \u001b[31m13.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m:00:01\u001b[0m00:01\u001b[0m\n",
      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m207.5/207.5 MB\u001b[0m \u001b[31m2.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m0:00:01\u001b[0m00:01\u001b[0m\n",
      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m21.1/21.1 MB\u001b[0m \u001b[31m11.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m:00:01\u001b[0m00:01\u001b[0m\n",
      "\u001b[?25h\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",
      "cesium 0.12.4 requires numpy<3.0,>=2.0, but you have numpy 1.26.4 which is incompatible.\n",
      "bigframes 1.42.0 requires rich<14,>=12.4.4, but you have rich 14.0.0 which is incompatible.\n",
      "gcsfs 2025.3.2 requires fsspec==2025.3.2, but you have fsspec 2025.3.0 which is incompatible.\u001b[0m\u001b[31m\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "# !pip install -q diffusers\n",
    "!pip install -q transformers accelerate scipy datasets peft==0.15.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "execution": {
     "iopub.execute_input": "2025-06-20T05:53:36.930940Z",
     "iopub.status.busy": "2025-06-20T05:53:36.930629Z",
     "iopub.status.idle": "2025-06-20T05:53:36.938132Z",
     "shell.execute_reply": "2025-06-20T05:53:36.937405Z",
     "shell.execute_reply.started": "2025-06-20T05:53:36.930902Z"
    },
    "executionInfo": {
     "elapsed": 34,
     "status": "ok",
     "timestamp": 1750132068621,
     "user": {
      "displayName": "Da T",
      "userId": "15660101803040065430"
     },
     "user_tz": -420
    },
    "id": "ror7up1gfhR-",
    "outputId": "35cd8d5b-f7fb-4448-a501-9e2417d18f76",
    "trusted": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/content/diffusers/examples/text_to_image\n"
     ]
    }
   ],
   "source": [
    "%cd diffusers/examples/text_to_image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 178,
     "status": "ok",
     "timestamp": 1750133770771,
     "user": {
      "displayName": "Da T",
      "userId": "15660101803040065430"
     },
     "user_tz": -420
    },
    "id": "rtSU4ZsHGcXy",
    "outputId": "82f0c536-8e79-424b-c75e-46d1682e955f"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatasetDict({\n",
       "    train: Dataset({\n",
       "        features: ['_data_files', '_fingerprint', '_format_columns', '_format_kwargs', '_format_type', '_output_all_columns', '_split'],\n",
       "        num_rows: 1\n",
       "    })\n",
       "})"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# dataset = load_dataset(\"./ghibli-dataset-local\")\n",
    "# dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "execution": {
     "iopub.execute_input": "2025-06-20T05:53:43.262117Z",
     "iopub.status.busy": "2025-06-20T05:53:43.261912Z",
     "iopub.status.idle": "2025-06-20T05:53:58.544457Z",
     "shell.execute_reply": "2025-06-20T05:53:58.543719Z",
     "shell.execute_reply.started": "2025-06-20T05:53:43.262094Z"
    },
    "executionInfo": {
     "elapsed": 15201,
     "status": "ok",
     "timestamp": 1750131452353,
     "user": {
      "displayName": "Da T",
      "userId": "15660101803040065430"
     },
     "user_tz": -420
    },
    "id": "RVHj1jG71HOa",
    "outputId": "bdfa832b-fb64-41b1-e897-154a204af33f",
    "trusted": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "accelerate configuration saved at /root/.cache/huggingface/accelerate/default_config.yaml\n"
     ]
    }
   ],
   "source": [
    "!accelerate config default"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "YChIG_a0Fd71"
   },
   "source": [
    "## SD-2.1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "execution": {
     "iopub.status.idle": "2025-06-20T16:59:43.087583Z",
     "shell.execute_reply": "2025-06-20T16:59:43.086720Z",
     "shell.execute_reply.started": "2025-06-20T05:53:58.545542Z"
    },
    "executionInfo": {
     "elapsed": 2786293,
     "status": "ok",
     "timestamp": 1750137852355,
     "user": {
      "displayName": "Da T",
      "userId": "15660101803040065430"
     },
     "user_tz": -420
    },
    "id": "umcNPYM-xZ6n",
    "outputId": "a664efa5-9742-4f7c-d6c1-3768be7287fc",
    "trusted": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Steps:  75%|█▌| 6000/7995 [8:16:17<2:39:44,  4.80s/it, lr=1e-5, step_loss=0.312]Model weights saved in Ghibli-Stable-Diffusion-2.1-LoRA-LoRA/checkpoint-6000/pytorch_lora_weights.safetensors\n",
      "Steps:  80%|█▌| 6396/7995 [8:48:01<1:39:52,  3.75s/it, lr=1e-5, step_loss=0.443]{'image_encoder'} was not found in config. Values will be initialized to default values.\n",
      "\n",
      "Loading pipeline components...:   0%|                     | 0/6 [00:00<?, ?it/s]\u001b[ALoaded feature_extractor as CLIPImageProcessor from `feature_extractor` subfolder of stabilityai/stable-diffusion-2-1.\n",
      "Loaded text_encoder as CLIPTextModel from `text_encoder` subfolder of stabilityai/stable-diffusion-2-1.\n",
      "\n",
      "Loading pipeline components...:  50%|██████▌      | 3/6 [00:00<00:00,  4.60it/s]\u001b[A{'clip_sample_range', 'rescale_betas_zero_snr', 'thresholding', 'timestep_spacing', 'dynamic_thresholding_ratio', 'sample_max_value'} was not found in config. Values will be initialized to default values.\n",
      "Loaded scheduler as DDIMScheduler from `scheduler` subfolder of stabilityai/stable-diffusion-2-1.\n",
      "Instantiating AutoencoderKL model under default dtype torch.float16.\n",
      "{'mid_block_add_attention', 'latents_mean', 'scaling_factor', 'latents_std', 'use_post_quant_conv', 'use_quant_conv', 'shift_factor', 'force_upcast'} was not found in config. Values will be initialized to default values.\n",
      "All model checkpoint weights were used when initializing AutoencoderKL.\n",
      "\n",
      "All the weights of AutoencoderKL were initialized from the model checkpoint at /root/.cache/huggingface/hub/models--stabilityai--stable-diffusion-2-1/snapshots/5cae40e6a2745ae2b01ad92ae5043f95f23644d6/vae.\n",
      "If your task is similar to the task the model of the checkpoint was trained on, you can already use AutoencoderKL for predictions without further training.\n",
      "Loaded vae as AutoencoderKL from `vae` subfolder of stabilityai/stable-diffusion-2-1.\n",
      "\n",
      "Loading pipeline components...:  83%|██████████▊  | 5/6 [00:00<00:00,  6.93it/s]\u001b[ALoaded tokenizer as CLIPTokenizer from `tokenizer` subfolder of stabilityai/stable-diffusion-2-1.\n",
      "Loading pipeline components...: 100%|█████████████| 6/6 [00:00<00:00,  7.05it/s]\n",
      "Steps:  87%|██▌| 6929/7995 [9:32:10<1:07:36,  3.81s/it, lr=1e-5, step_loss=0.31]{'image_encoder'} was not found in config. Values will be initialized to default values.\n",
      "\n",
      "Loading pipeline components...:   0%|                     | 0/6 [00:00<?, ?it/s]\u001b[ALoaded feature_extractor as CLIPImageProcessor from `feature_extractor` subfolder of stabilityai/stable-diffusion-2-1.\n",
      "Loaded text_encoder as CLIPTextModel from `text_encoder` subfolder of stabilityai/stable-diffusion-2-1.\n",
      "\n",
      "Loading pipeline components...:  50%|██████▌      | 3/6 [00:01<00:01,  2.46it/s]\u001b[A{'clip_sample_range', 'rescale_betas_zero_snr', 'thresholding', 'timestep_spacing', 'dynamic_thresholding_ratio', 'sample_max_value'} was not found in config. Values will be initialized to default values.\n",
      "Loaded scheduler as DDIMScheduler from `scheduler` subfolder of stabilityai/stable-diffusion-2-1.\n",
      "Instantiating AutoencoderKL model under default dtype torch.float16.\n",
      "{'mid_block_add_attention', 'latents_mean', 'scaling_factor', 'latents_std', 'use_post_quant_conv', 'use_quant_conv', 'shift_factor', 'force_upcast'} was not found in config. Values will be initialized to default values.\n",
      "All model checkpoint weights were used when initializing AutoencoderKL.\n",
      "\n",
      "All the weights of AutoencoderKL were initialized from the model checkpoint at /root/.cache/huggingface/hub/models--stabilityai--stable-diffusion-2-1/snapshots/5cae40e6a2745ae2b01ad92ae5043f95f23644d6/vae.\n",
      "If your task is similar to the task the model of the checkpoint was trained on, you can already use AutoencoderKL for predictions without further training.\n",
      "Loaded vae as AutoencoderKL from `vae` subfolder of stabilityai/stable-diffusion-2-1.\n",
      "\n",
      "Loading pipeline components...:  83%|██████████▊  | 5/6 [00:01<00:00,  4.05it/s]\u001b[ALoaded tokenizer as CLIPTokenizer from `tokenizer` subfolder of stabilityai/stable-diffusion-2-1.\n",
      "Loading pipeline components...: 100%|█████████████| 6/6 [00:01<00:00,  4.13it/s]\n",
      "Steps:  88%|███▌| 7000/7995 [9:39:22<1:20:42,  4.87s/it, lr=1e-5, step_loss=0.4]Model weights saved in Ghibli-Stable-Diffusion-2.1-LoRA-LoRA/checkpoint-7000/pytorch_lora_weights.safetensors\n",
      "Steps:  93%|██▊| 7462/7995 [10:16:33<33:38,  3.79s/it, lr=1e-5, step_loss=0.434]{'image_encoder'} was not found in config. Values will be initialized to default values.\n",
      "\n",
      "Loading pipeline components...:   0%|                     | 0/6 [00:00<?, ?it/s]\u001b[ALoaded feature_extractor as CLIPImageProcessor from `feature_extractor` subfolder of stabilityai/stable-diffusion-2-1.\n",
      "Loaded text_encoder as CLIPTextModel from `text_encoder` subfolder of stabilityai/stable-diffusion-2-1.\n",
      "\n",
      "Loading pipeline components...:  50%|██████▌      | 3/6 [00:00<00:00,  3.99it/s]\u001b[A{'clip_sample_range', 'rescale_betas_zero_snr', 'thresholding', 'timestep_spacing', 'dynamic_thresholding_ratio', 'sample_max_value'} was not found in config. Values will be initialized to default values.\n",
      "Loaded scheduler as DDIMScheduler from `scheduler` subfolder of stabilityai/stable-diffusion-2-1.\n",
      "Instantiating AutoencoderKL model under default dtype torch.float16.\n",
      "{'mid_block_add_attention', 'latents_mean', 'scaling_factor', 'latents_std', 'use_post_quant_conv', 'use_quant_conv', 'shift_factor', 'force_upcast'} was not found in config. Values will be initialized to default values.\n",
      "All model checkpoint weights were used when initializing AutoencoderKL.\n",
      "\n",
      "All the weights of AutoencoderKL were initialized from the model checkpoint at /root/.cache/huggingface/hub/models--stabilityai--stable-diffusion-2-1/snapshots/5cae40e6a2745ae2b01ad92ae5043f95f23644d6/vae.\n",
      "If your task is similar to the task the model of the checkpoint was trained on, you can already use AutoencoderKL for predictions without further training.\n",
      "Loaded vae as AutoencoderKL from `vae` subfolder of stabilityai/stable-diffusion-2-1.\n",
      "\n",
      "Loading pipeline components...:  83%|██████████▊  | 5/6 [00:00<00:00,  6.01it/s]\u001b[ALoaded tokenizer as CLIPTokenizer from `tokenizer` subfolder of stabilityai/stable-diffusion-2-1.\n",
      "Loading pipeline components...: 100%|█████████████| 6/6 [00:00<00:00,  6.14it/s]\n",
      "Steps: 100%|███| 7995/7995 [11:00:49<00:00,  3.74s/it, lr=1e-5, step_loss=0.375]{'image_encoder'} was not found in config. Values will be initialized to default values.\n",
      "\n",
      "Loading pipeline components...:   0%|                     | 0/6 [00:00<?, ?it/s]\u001b[ALoaded feature_extractor as CLIPImageProcessor from `feature_extractor` subfolder of stabilityai/stable-diffusion-2-1.\n",
      "Loaded text_encoder as CLIPTextModel from `text_encoder` subfolder of stabilityai/stable-diffusion-2-1.\n",
      "\n",
      "Loading pipeline components...:  50%|██████▌      | 3/6 [00:00<00:00,  3.98it/s]\u001b[A{'clip_sample_range', 'rescale_betas_zero_snr', 'thresholding', 'timestep_spacing', 'dynamic_thresholding_ratio', 'sample_max_value'} was not found in config. Values will be initialized to default values.\n",
      "Loaded scheduler as DDIMScheduler from `scheduler` subfolder of stabilityai/stable-diffusion-2-1.\n",
      "Instantiating AutoencoderKL model under default dtype torch.float16.\n",
      "{'mid_block_add_attention', 'latents_mean', 'scaling_factor', 'latents_std', 'use_post_quant_conv', 'use_quant_conv', 'shift_factor', 'force_upcast'} was not found in config. Values will be initialized to default values.\n",
      "All model checkpoint weights were used when initializing AutoencoderKL.\n",
      "\n",
      "All the weights of AutoencoderKL were initialized from the model checkpoint at /root/.cache/huggingface/hub/models--stabilityai--stable-diffusion-2-1/snapshots/5cae40e6a2745ae2b01ad92ae5043f95f23644d6/vae.\n",
      "If your task is similar to the task the model of the checkpoint was trained on, you can already use AutoencoderKL for predictions without further training.\n",
      "Loaded vae as AutoencoderKL from `vae` subfolder of stabilityai/stable-diffusion-2-1.\n",
      "\n",
      "Loading pipeline components...:  83%|██████████▊  | 5/6 [00:00<00:00,  6.01it/s]\u001b[ALoaded tokenizer as CLIPTokenizer from `tokenizer` subfolder of stabilityai/stable-diffusion-2-1.\n",
      "Loading pipeline components...: 100%|█████████████| 6/6 [00:00<00:00,  6.16it/s]\n",
      "Model weights saved in Ghibli-Stable-Diffusion-2.1-LoRA-LoRA/pytorch_lora_weights.safetensors\n",
      "{'image_encoder'} was not found in config. Values will be initialized to default values.\n",
      "\n",
      "Loading pipeline components...:   0%|                     | 0/6 [00:00<?, ?it/s]\u001b[AInstantiating UNet2DConditionModel model under default dtype torch.float16.\n",
      "{'reverse_transformer_layers_per_block', 'encoder_hid_dim', 'timestep_post_act', 'resnet_time_scale_shift', 'num_attention_heads', 'cross_attention_norm', 'resnet_skip_time_act', 'class_embed_type', 'conv_in_kernel', 'mid_block_only_cross_attention', 'addition_embed_type', 'encoder_hid_dim_type', 'addition_embed_type_num_heads', 'projection_class_embeddings_input_dim', 'dropout', 'mid_block_type', 'transformer_layers_per_block', 'attention_type', 'resnet_out_scale_factor', 'time_embedding_type', 'time_embedding_dim', 'time_cond_proj_dim', 'conv_out_kernel', 'time_embedding_act_fn', 'class_embeddings_concat', 'addition_time_embed_dim'} was not found in config. Values will be initialized to default values.\n",
      "All model checkpoint weights were used when initializing UNet2DConditionModel.\n",
      "\n",
      "All the weights of UNet2DConditionModel were initialized from the model checkpoint at /root/.cache/huggingface/hub/models--stabilityai--stable-diffusion-2-1/snapshots/5cae40e6a2745ae2b01ad92ae5043f95f23644d6/unet.\n",
      "If your task is similar to the task the model of the checkpoint was trained on, you can already use UNet2DConditionModel for predictions without further training.\n",
      "Loaded unet as UNet2DConditionModel from `unet` subfolder of stabilityai/stable-diffusion-2-1.\n",
      "\n",
      "Loading pipeline components...:  17%|██▏          | 1/6 [00:08<00:43,  8.67s/it]\u001b[ALoaded feature_extractor as CLIPImageProcessor from `feature_extractor` subfolder of stabilityai/stable-diffusion-2-1.\n",
      "Loaded text_encoder as CLIPTextModel from `text_encoder` subfolder of stabilityai/stable-diffusion-2-1.\n",
      "\n",
      "Loading pipeline components...:  50%|██████▌      | 3/6 [00:09<00:07,  2.58s/it]\u001b[A{'clip_sample_range', 'rescale_betas_zero_snr', 'thresholding', 'timestep_spacing', 'dynamic_thresholding_ratio', 'sample_max_value'} was not found in config. Values will be initialized to default values.\n",
      "Loaded scheduler as DDIMScheduler from `scheduler` subfolder of stabilityai/stable-diffusion-2-1.\n",
      "Instantiating AutoencoderKL model under default dtype torch.float16.\n",
      "{'mid_block_add_attention', 'latents_mean', 'scaling_factor', 'latents_std', 'use_post_quant_conv', 'use_quant_conv', 'shift_factor', 'force_upcast'} was not found in config. Values will be initialized to default values.\n",
      "All model checkpoint weights were used when initializing AutoencoderKL.\n",
      "\n",
      "All the weights of AutoencoderKL were initialized from the model checkpoint at /root/.cache/huggingface/hub/models--stabilityai--stable-diffusion-2-1/snapshots/5cae40e6a2745ae2b01ad92ae5043f95f23644d6/vae.\n",
      "If your task is similar to the task the model of the checkpoint was trained on, you can already use AutoencoderKL for predictions without further training.\n",
      "Loaded vae as AutoencoderKL from `vae` subfolder of stabilityai/stable-diffusion-2-1.\n",
      "\n",
      "Loading pipeline components...:  83%|██████████▊  | 5/6 [00:09<00:01,  1.29s/it]\u001b[ALoaded tokenizer as CLIPTokenizer from `tokenizer` subfolder of stabilityai/stable-diffusion-2-1.\n",
      "Loading pipeline components...: 100%|█████████████| 6/6 [00:09<00:00,  1.63s/it]\n",
      "Loading unet.\n",
      "No LoRA keys associated to CLIPTextModel found with the prefix='text_encoder'. This is safe to ignore if LoRA state dict didn't originally have any CLIPTextModel related params. You can also try specifying `prefix=None` to resolve the warning. Otherwise, open an issue if you think it's unexpected: https://github.com/huggingface/diffusers/issues/new\n",
      "Steps: 100%|███| 7995/7995 [11:03:53<00:00,  4.98s/it, lr=1e-5, step_loss=0.375]\n"
     ]
    }
   ],
   "source": [
    "!export WANDB_MODE=disabled\n",
    "\n",
    "!accelerate launch train_text_to_image_lora.py \\\n",
    "    --pretrained_model_name_or_path=\"stabilityai/stable-diffusion-2-1\" \\\n",
    "    --dataset_name=\"pulnip/ghibli-dataset\" \\\n",
    "    --image_column=\"image\" \\\n",
    "    --caption_column=\"description\" \\\n",
    "    --mixed_precision=\"fp16\" \\\n",
    "    --lr_warmup_steps=400 \\\n",
    "    --num_train_epochs=15 \\\n",
    "    --resolution=512 \\\n",
    "    --random_flip \\\n",
    "    --train_batch_size=4 \\\n",
    "    --gradient_accumulation_steps=2 \\\n",
    "    --checkpointing_steps=1000 \\\n",
    "    --learning_rate=1e-05 \\\n",
    "    --checkpoints_total_limit=1\\\n",
    "    --lr_scheduler=\"constant\" \\\n",
    "    --seed=42 \\\n",
    "    --output_dir=\"Ghibli-Stable-Diffusion-2.1-LoRA\" \\\n",
    "    --validation_prompt=\"A whimsical Ghibli-style scene\"\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "HkkScKvS3sOd"
   },
   "source": [
    "# Inference"
   ]
  },
  {
   "cell_type": "code",
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    "execution": {
     "iopub.execute_input": "2025-06-20T17:06:38.928062Z",
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     "iopub.status.idle": "2025-06-20T17:06:38.948197Z",
     "shell.execute_reply": "2025-06-20T17:06:38.947039Z",
     "shell.execute_reply.started": "2025-06-20T17:06:38.928035Z"
    },
    "executionInfo": {
     "elapsed": 7011,
     "status": "ok",
     "timestamp": 1750137859911,
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      "displayName": "Da T",
      "userId": "15660101803040065430"
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     "user_tz": -420
    },
    "id": "pckAs1B63wKf",
    "outputId": "48c000b2-7252-4732-895c-a6f0b78f4dda",
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   "outputs": [],
   "source": [
    "import torch\n",
    "from diffusers import StableDiffusionPipeline, DPMSolverMultistepScheduler\n",
    "base_model = \"stabilityai/stable-diffusion-2-1\"\n",
    "lora_model = \"ckpts/Ghibli-Stable-Diffusion-2.1-LoRA\"\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pipe = StableDiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.float16)\n",
    "pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)\n",
    "\n",
    "# Add LoRA weights with specified rank and scale\n",
    "pipe.load_lora_weights(lora_model, adapter_name=\"ghibli-lora\", lora_scale=0.8)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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    "colab": {
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   "outputs": [],
   "source": [
    "pipe.unet.load_attn_procs(lora_model)\n",
    "pipe.to(\"cuda\")\n",
    "\n",
    "image = pipe(\"a girl is on a street on a beach\", num_inference_steps=25).images[0]\n",
    "image"
   ]
  }
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