Delete donut_train.ipynb

donut_train.ipynb

@@ -1,110 +0,0 @@
-{
-  "cells": [
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "-BZ2HFB9OtWP"
-      },
-      "outputs": [],
-      "source": [
-        "from google.colab import drive\n",
-        "drive.mount('/content/drive')\n",
-        "%cd /content/drive/MyDrive/donut"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "colab": {
-          "background_save": true
-        },
-        "id": "SJpD4AAj7qeZ"
-      },
-      "outputs": [],
-      "source": [
-        "!pip install transformers==4.25.1\n",
-        "!pip install timm==0.5.4\n",
-        "!pip install donut-python"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "source": [
-        "from donut import DonutModel\n",
-        "from PIL import Image\n",
-        "import torch"
-      ],
-      "metadata": {
-        "id": "PxFaO3rfDHQJ"
-      },
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "Ro21MdJPSTZs"
-      },
-      "outputs": [],
-      "source": [
-        "# Copy one default config yaml file and amend to fit your use case.\n",
-        "!python train.py --config ./config/train_Booking.yaml"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "J1ITHX4jV2Go"
-      },
-      "outputs": [],
-      "source": [
-        "# After train, you can evaluate and use the model.\n",
-        "\n",
-        "model = DonutModel.from_pretrained(\"/content/drive/MyDrive/donut/result/train_Booking/20240327_032854\")\n",
-        "if torch.cuda.is_available():\n",
-        "    model.half()\n",
-        "    device = torch.device(\"cuda\")\n",
-        "    model.to(device)\n",
-        "else:\n",
-        "    model.encoder.to(torch.bfloat16)\n",
-        "\n",
-        "model.eval()"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "2UhjFTmrWIrX"
-      },
-      "outputs": [],
-      "source": [
-        "image = Image.open(\"/content/COSCO_000.jpg\").convert(\"RGB\")\n",
-        "with torch.no_grad():\n",
-        "  # My dataset name is Booking , tag i.e. <s_Booking>\n",
-        "  output = model.inference(image=image, prompt=\"<s_Booking>\")\n",
-        "output"
-      ]
-    }
-  ],
-  "metadata": {
-    "accelerator": "GPU",
-    "colab": {
-      "gpuType": "V100",
-      "provenance": []
-    },
-    "kernelspec": {
-      "display_name": "Python 3",
-      "name": "python3"
-    },
-    "language_info": {
-      "name": "python"
-    }
-  },
-  "nbformat": 4,
-  "nbformat_minor": 0
-}