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"visibility": null, "width": null } }, "b71c6d0f87d141dab23daee608658265": { "model_module": "@jupyter-widgets/controls", "model_name": "DescriptionStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } } } } }, "cells": [ { "cell_type": "markdown", "source": [ "## Install the modified `dom-tokenizers`" ], "metadata": { "id": "p4cA_Al2R8Fm" } }, { "cell_type": "code", "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "AxuqwFstR6UD", "outputId": "62559b3c-9a50-433b-bd7e-e46adb634347" }, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Cloning into 'dom-tokenizers'...\n", "remote: Enumerating objects: 571, done.\u001b[K\n", "remote: Counting objects: 100% (145/145), done.\u001b[K\n", "remote: Compressing objects: 100% (59/59), done.\u001b[K\n", "remote: Total 571 (delta 94), reused 110 (delta 81), pack-reused 426\u001b[K\n", "Receiving objects: 100% (571/571), 141.07 KiB | 8.30 MiB/s, done.\n", "Resolving deltas: 100% (311/311), done.\n" ] } ], "source": [ "!git clone https://github.com/gbenson/dom-tokenizers.git -b emit-unique-tokens-0.0.17 --single-branch" ] }, { "cell_type": "code", "source": [ "!cd dom-tokenizers && pip install -e .[train]" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "iURZKR40UCxY", "outputId": "15b2a8f4-9bc6-4752-b6b7-5a80561acb7e", "collapsed": true }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Obtaining file:///content/dom-tokenizers\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 ... 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python-dateutil>=2.8.2->pandas->datasets->dom-tokenizers==0.0.17) (1.16.0)\n", "Building wheels for collected packages: dom-tokenizers\n", " Building editable for dom-tokenizers (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n", " Created wheel for dom-tokenizers: filename=dom_tokenizers-0.0.17-0.editable-py3-none-any.whl size=7355 sha256=c029c52ddfa3cce2ecfc0f7342d044c8d7f94e81ac10d04a6ba2c521d87471a7\n", " Stored in directory: /tmp/pip-ephem-wheel-cache-aciag458/wheels/ab/e4/d2/9b9419db21d26514602a3dbb7582a3c195f9229169192ca43b\n", "Successfully built dom-tokenizers\n", "Installing collected packages: xxhash, unidecode, requests, python-magic, pyarrow, dill, multiprocess, dom-tokenizers, datasets\n", " Attempting uninstall: requests\n", " Found existing installation: requests 2.31.0\n", " Uninstalling requests-2.31.0:\n", " Successfully uninstalled requests-2.31.0\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", "\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 16.1.0 which is incompatible.\n", "google-colab 1.0.0 requires requests==2.31.0, but you have requests 2.32.3 which is incompatible.\n", "ibis-framework 8.0.0 requires pyarrow<16,>=2, but you have pyarrow 16.1.0 which is incompatible.\u001b[0m\u001b[31m\n", "\u001b[0mSuccessfully installed datasets-2.20.0 dill-0.3.8 dom-tokenizers-0.0.17 multiprocess-0.70.16 pyarrow-16.1.0 python-magic-0.4.27 requests-2.32.3 unidecode-1.3.8 xxhash-3.4.1\n" ] } ] }, { "cell_type": "markdown", "source": [ "## Train a tokenizer on `gbenson/webui-dom-snapshots`\n", "\n", "We don't need the tokenizer, but this `dom-tokenizers` is modified to output every unique token it sees into a file as a side-effect." ], "metadata": { "id": "aXQW8CBmVOa4" } }, { "cell_type": "code", "source": [ "!train-tokenizer -n30000 -N4536 gbenson/webui-dom-snapshots" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "CqHIS-8xVVKe", "outputId": "13ab413c-2efe-4620-ebe6-68af0b175504" }, "execution_count": 3, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Output directory: /content/dom-tokenizer-30k\n", "\n", "Downloading readme: 100% 9.16k/9.16k [00:00<00:00, 29.9MB/s]\n", "tokenizer_config.json: 100% 48.0/48.0 [00:00<00:00, 314kB/s]\n", "config.json: 100% 570/570 [00:00<00:00, 4.00MB/s]\n", "vocab.txt: 100% 232k/232k [00:00<00:00, 25.2MB/s]\n", "tokenizer.json: 100% 466k/466k [00:00<00:00, 28.4MB/s]\n", "Generating up to 30,000 tokens from 4,536 examples:\n", "\u001b[2K[00:00:02] Tokenize words ██████████████████ 923123 / 923123\n", "\u001b[2K[00:01:13] Count pairs ██████████████████ 923123 / 923123\n", "\u001b[2K[00:00:14] Compute merges ██████████████████ 23913 / 23913\n", "\n", "['training', 'complete']\n", "['token', '##izer', 'state', 'saved']\n", "['see', 'you', 'soon', '##!', '##!']\n" ] } ] }, { "cell_type": "markdown", "source": [ "## Load the file into a dataset" ], "metadata": { "id": "Uo_FraY1W5IK" } }, { "cell_type": "code", "source": [ "from datasets import load_dataset\n", "dataset = load_dataset(\"text\", data_files={\"train\": [\"unique-tokens\"]})" ], "metadata": { "id": "L_oxSzmFW-nL", "colab": { "base_uri": "https://localhost:8080/", "height": 49, "referenced_widgets": [ "11453f78da7b4a68a71b0ffe39fcf03e", "1a46540797bf40d3a58b961e98e98ee4", "0abed8e50eda4f1db7f5999a19bfcdc2", "fe41e28c1c4c49948a92ee07fe212232", "c63df90dbc754ce39245e44d30fa9598", "2440d614a00f45eda293a3437bcab703", "98dc558e0e2a4f7caea5bd30dd4c94ba", "d0c95ba2f52b48ae8e0985103dbdf913", "67369023f7d544e1845b505ec7c6036f", "bae6e90637f94f108291bf5980fdb4b6", "0c38dc7aa8dc4587aeb076dcd84f91ee" ] }, "outputId": "aa4f0347-7e15-479c-e762-2597675dc3b1" }, "execution_count": 4, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "Generating train split: 0 examples [00:00, ? examples/s]" ], "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, "model_id": "11453f78da7b4a68a71b0ffe39fcf03e" } }, "metadata": {} } ] }, { "cell_type": "markdown", "source": [ "## Upload to Hugging Face" ], "metadata": { "id": "sqbaaByQYG5q" } }, { "cell_type": "code", "source": [ "dataset.push_to_hub(\"gbenson/webui-tokens-unlabelled\")" ], "metadata": { "id": "ICObGLZvYHRZ", "colab": { "base_uri": "https://localhost:8080/", "height": 149, "referenced_widgets": [ "9b434c8f7a92462ea0d62105c7058828", "7186b7c3d60249f08640e749d0706e69", "34fac37a82724859ade36d38ae414e13", "11050510fb2a482a9029bc47efb36f5e", "e420a8b5976f4a03900272883ff9a13d", "0a171d0b29214625b37d58ca8e7e7d72", "be1bfb31bf104e3cb0b4c0409897f058", "a82f06e14fba4a2cb76152eaba39d180", "4d26135cfb7144d48face390e4605a5a", "ced312f813b64cc894810fc49efa1d5c", "aed04606a80f40529088d252b8ec58be", "eeaba6b9bc3040edb5ceb7407de6e3a3", "44951ec735f044bd9d96df64be505254", "9196028674af43b2bac42ba79e2236ff", "e2bb507bbdb043a483aefe39957e39d0", "9a64866058e34023a1257f13bffb3848", "5484e5fe36d4468e86bebed912950202", "7dc59ee3ba544859bcf88823390eed66", "4f53cd9c6d0b4edb931a38e10339d15a", "1e0deb27ec434efd90524c4c5f172453", "de0113aa335a4611978c78c1e4f96bb6", "820d2fb899424338a8da219259f76a80", "af0998ae0102414f82f0975be46e270a", "0407df9f0b6040f586c6645cbfcaa5f0", "5325510517b34060aa525a2a83a5607f", "ee1bae8563404a9e94062d4d5e497c5b", "cad6fe2cd554475ba0ea06e731ed4ebe", "7af597ac9ccc4d21966947f9a36556c0", "278355ab308d403a89906612dac2f727", "9efa132daa664f168ed92938c0c90e38", "5cbc02bb060e46a9b8c3fd97c93f5068", "120f433516e54a14bc948ad1687681f5", "b71c6d0f87d141dab23daee608658265" ] }, "outputId": "547fa3c3-96a7-4c3f-b24c-fb1f2948f165" }, "execution_count": 5, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "Uploading the dataset shards: 0%| | 0/1 [00:00