Super-squash branch 'main' using huggingface_hub

.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
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+*.h5 filter=lfs diff=lfs merge=lfs -text
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+*.model filter=lfs diff=lfs merge=lfs -text
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+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
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+*tfevents* filter=lfs diff=lfs merge=lfs -text
+# Audio files - uncompressed
+*.pcm filter=lfs diff=lfs merge=lfs -text
+*.sam filter=lfs diff=lfs merge=lfs -text
+*.raw filter=lfs diff=lfs merge=lfs -text
+# Audio files - compressed
+*.aac filter=lfs diff=lfs merge=lfs -text
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+*.mp3 filter=lfs diff=lfs merge=lfs -text
+*.ogg filter=lfs diff=lfs merge=lfs -text
+*.wav filter=lfs diff=lfs merge=lfs -text
+# Image files - uncompressed
+*.bmp filter=lfs diff=lfs merge=lfs -text
+*.gif filter=lfs diff=lfs merge=lfs -text
+*.png filter=lfs diff=lfs merge=lfs -text
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+# Image files - compressed
+*.jpg filter=lfs diff=lfs merge=lfs -text
+*.jpeg filter=lfs diff=lfs merge=lfs -text
+*.webp filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+language:
+- en
+- es
+- fi
+- fr
+- pt
+- nl
+- de
+- sv
+- it
+license: odc-by
+size_categories:
+- 1K<n<10K
+task_categories:
+- text-generation
+- feature-extraction
+dataset_info:
+- config_name: default
+  features:
+  - name: filename
+    dtype: string
+  - name: text
+    dtype: string
+  - name: lang
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 2190406903
+    num_examples: 4999
+  download_size: 1310735987
+  dataset_size: 2190406903
+- config_name: en-clean
+  features:
+  - name: filename
+    dtype: string
+  - name: text
+    dtype: string
+  - name: lang
+    dtype: string
+  - name: score
+    dtype: float64
+  splits:
+  - name: train
+    num_bytes: 1948279468.5718827
+    num_examples: 4371
+  download_size: 1167660575
+  dataset_size: 1948279468.5718827
+- config_name: english
+  features:
+  - name: filename
+    dtype: string
+  - name: text
+    dtype: string
+  - name: lang
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 1929258170.415883
+    num_examples: 4403
+  download_size: 1172514726
+  dataset_size: 1929258170.415883
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-*
+- config_name: en-clean
+  data_files:
+  - split: train
+    path: en-clean/train-*
+- config_name: english
+  data_files:
+  - split: train
+    path: english/train-*
+tags:
+- gutenberg
+- epub
+- marker
+---
+
+# BEE-spoke-data/napierone-epub-raw
+
+NapierOne [EPUB files](http://napierone.com.s3-eu-north-1.amazonaws.com/NapierOne/Data/EPUB/) converted with [marker](https://github.com/VikParuchuri/marker/tree/master). Seems to contain mostly books from Project Gutenberg.
+
+## detected languages
+
+via fasttext-langdetect
+
+```py
+{'ca': 1,
+ 'cy': 1,
+ 'da': 6,
+ 'de': 105,
+ 'en': 4403,
+ 'eo': 2,
+ 'es': 61,
+ 'fi': 76,
+ 'fr': 189,
+ 'he': 1,
+ 'hu': 5,
+ 'is': 1,
+ 'it': 40,
+ 'la': 6,
+ 'nl': 41,
+ 'pl': 4,
+ 'pt': 38,
+ 'sv': 10,
+ 'tl': 9}
+```

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marker_pdf_conversion.ipynb

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+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "source": [
+        "# marker pdf conversion\n",
+        "\n",
+        "\n",
+        "- https://github.com/VikParuchuri/marker/tree/master\n",
+        "\n",
+        "\n",
+        "---"
+      ],
+      "metadata": {
+        "id": "PzogeOQ6rbvL"
+      }
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "lIYdn1woOS1n"
+      },
+      "outputs": [],
+      "source": [
+        "!git clone https://github.com/VikParuchuri/marker.git\n",
+        "%cd marker"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "!pip install -U -q pip ninja poetry"
+      ],
+      "metadata": {
+        "id": "YkbBuXMudX5g"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "%%bash\n",
+        "set -e\n",
+        "sudo apt-get update\n",
+        "sudo apt-get install -y software-properties-common\n",
+        "sudo apt-get install -y build-essential python3 python3-pip git\n",
+        "sudo apt-get install -y python3-dev libssl-dev libc6-dev && sudo apt install zip unzip tmux nano p7zip-full git -y\n",
+        "clear\n",
+        "echo \"done\""
+      ],
+      "metadata": {
+        "id": "JzW38yGYhH3W"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "# %%bash\n",
+        "!sudo apt update && sudo apt upgrade -y > /dev/null\n",
+        "!bash scripts/install/tesseract_5_install.sh\n",
+        "# !bash scripts/install/ghostscript_install.sh && clear\n",
+        "!sudo apt install ghostscript && clear\n",
+        "!cat scripts/install/apt-requirements.txt | xargs sudo apt install -y --allow-unauthenticated > LOG_installs_apt.log"
+      ],
+      "metadata": {
+        "id": "cDcjkP3hd_Kh"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "%%writefile convert_pdf_dir.sh\n",
+        "#@title convert_pdf_dir.sh\n",
+        "#!/bin/bash\n",
+        "\n",
+        "# Default source directory is the current directory if not specified\n",
+        "SOURCE_DIR=${1:-$(pwd)}\n",
+        "# Default target directory is parent of source directory + marker-pdf2text\n",
+        "TARGET_DIR=${2:-$(dirname \"$(realpath $SOURCE_DIR)\")/marker-pdf2text}\n",
+        "\n",
+        "# Function to convert a single PDF file\n",
+        "convert_pdf() {\n",
+        "    local source_pdf=$1\n",
+        "    local target_md=$2\n",
+        "    mkdir -p \"$(dirname \"$target_md\")\" # Ensure the target directory exists\n",
+        "    poetry run python convert_single.py \"$source_pdf\" \"$target_md\"\n",
+        "}\n",
+        "\n",
+        "export -f convert_pdf\n",
+        "\n",
+        "# Find all PDF files and convert them\n",
+        "find \"$SOURCE_DIR\" -type f -name '*.pdf' -exec bash -c 'convert_pdf \"$0\" \"${1/pdf/md}\"' {} \"$TARGET_DIR/$(realpath --relative-to=\"$SOURCE_DIR\" \"{}\")\" \\;\n",
+        "\n",
+        "echo \"Conversion complete. All markdown files have been saved to $TARGET_DIR.\""
+      ],
+      "metadata": {
+        "cellView": "form",
+        "id": "aRi6CBR_ekIw"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "!find / -name tessdata\n",
+        "!echo \"TESSDATA_PREFIX=/usr/share/tesseract-ocr/5/tessdata\" > local.env\n",
+        "!sudo rm *.lock\n",
+        "!poetry install -q"
+      ],
+      "metadata": {
+        "id": "TlQ6wV_Lfawh",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "299eca48-79ba-41a3-95c1-7b5ffc657b14"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "\u001b[1A\u001b[0J  \u001b[34;1m-\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtorch\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+            "\u001b[1A\u001b[0J  \u001b[32;1m-\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtorch\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.3.0\u001b[39m\u001b[39m)\u001b[39m\n",
+            "\n",
+            "\u001b[34mWriting lock file\u001b[39m\n",
+            "\n",
+            "\u001b[39;1mInstalling\u001b[39;22m the current project: \u001b[36mmarker-pdf\u001b[39m (\u001b[39;1m0.1.3\u001b[39;22m)\u001b[1G\u001b[2K\u001b[39;1mInstalling\u001b[39;22m the current project: \u001b[36mmarker-pdf\u001b[39m (\u001b[32m0.1.3\u001b[39m)\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "---"
+      ],
+      "metadata": {
+        "id": "jNOFjXVJSz2L"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "## from dropbox\n"
+      ],
+      "metadata": {
+        "id": "yn0qVN93V0v6"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "URL = \"https://www.dropbox.com/scl/fo/kbbliz7or5ptwc1c7vgb9/AF0b76tmbY3BuxHDnMzNO1E?rlkey=x5q3r7o9wdob85xjazjanloe3&dl=1\" # @param {type:\"string\"}\n",
+        "!wget -q -O data.zip $URL\n",
+        "!unzip data.zip -d /content/pdf-textbooks\n",
+        "!rm data.zip && clear"
+      ],
+      "metadata": {
+        "id": "YwnblF4_iZuu"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "# !bash convert_pdf_dir.sh /content/pdf-textbooks"
+      ],
+      "metadata": {
+        "id": "MmkB5ix-imgH"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "!DEFAULT_LANG=\"en\" TORCH_DEVICE=cuda poetry run python convert.py\\\n",
+        "    /content/pdf-textbooks/python-book \\\n",
+        "    /content/marker-md2text/python-book \\\n",
+        "    --workers 6 --min_length 100"
+      ],
+      "metadata": {
+        "id": "GWZURJALmDtV"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "out_file=\"/content/archived-all-marker.7z\"\n",
+        "!find /content/marker-md2text -type f -name \"*.json\" -print -delete # fuck off\n",
+        "!7z a $out_file /content/marker-md2text"
+      ],
+      "metadata": {
+        "id": "c5xndco3mJdq"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "## napierone"
+      ],
+      "metadata": {
+        "id": "qybBz9Oqp2pH"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "target_dir = '/content/napierone-epub'\n",
+        "!wget -q http://napierone.com.s3-eu-north-1.amazonaws.com/NapierOne/Data/EPUB/EPUB-total.zip\n",
+        "!unzip -o -q EPUB-total.zip -d $target_dir\n",
+        "!ls $target_dir | wc -l\n",
+        "!rm *.zip"
+      ],
+      "metadata": {
+        "id": "jhB5lOA6n8f5"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "!DEFAULT_LANG=\"en\" TORCH_DEVICE=cuda poetry run python convert.py\\\n",
+        "    $target_dir \\\n",
+        "    /content/marker-napierone-file2text/EPUB \\\n",
+        "    --workers 6 --min_length 300"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "Poi65wYSpryu",
+        "outputId": "8a20c15e-ae37-4be3-85e8-be3dea88afb8"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "metadata": {
+            "tags": null
+          },
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "2024-05-08 22:37:05,427\tINFO worker.py:1749 -- Started a local Ray instance.\n",
+            "Loaded texify model to cuda with torch.float16 dtype\n",
+            "Converting 5000 pdfs in chunk 1/1 with 6 processes, and storing in /content/marker-napierone-file2text/EPUB\n",
+            "100% 4999/5000 [14:01:52<00:08,  8.66s/it]"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "out_file=\"/content/archived-marker-napierone-epub.7z\"\n",
+        "!find /content/marker-napierone-file2text -type f -name \"*.json\" -print -delete # fuck off\n",
+        "!7z a $out_file /content/marker-napierone-file2text"
+      ],
+      "metadata": {
+        "id": "sU8QpnNStjFn"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "from google.colab import files\n",
+        "files.download(out_file)"
+      ],
+      "metadata": {
+        "id": "iyzMPMmtqAzI"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [],
+      "metadata": {
+        "id": "CiYoo9ZEtrEz"
+      },
+      "execution_count": null,
+      "outputs": []
+    }
+  ],
+  "metadata": {
+    "colab": {
+      "provenance": [],
+      "gpuType": "L4",
+      "machine_shape": "hm"
+    },
+    "kernelspec": {
+      "display_name": "Python 3",
+      "name": "python3"
+    },
+    "accelerator": "GPU"
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}