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Upload flan_t5_large의_그래머_검사기.ipynb
Browse files- flan_t5_large의_그래머_검사기.ipynb +2413 -0
flan_t5_large의_그래머_검사기.ipynb
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|
| 1 |
+
{
|
| 2 |
+
"cells": [
|
| 3 |
+
{
|
| 4 |
+
"cell_type": "markdown",
|
| 5 |
+
"source": [
|
| 6 |
+
"# <center> demo for `pszemraj/flan-t5-large-grammar-synthesis`\n",
|
| 7 |
+
"\n",
|
| 8 |
+
"\n",
|
| 9 |
+
"- this notebook runs on CPU by default. use google or chatGPT to figure out how to change that if you want to run on GPU\n",
|
| 10 |
+
"- some details on usage\n",
|
| 11 |
+
" - this model was trained on several (1-8) sentences at a time. \n",
|
| 12 |
+
" - by default, it **will not** work well for super low token counts (like 4) or super long texts\n",
|
| 13 |
+
" - I would recommend using it in batches of 4-128 tokens at a time\n",
|
| 14 |
+
" - an **extension** of this notebook for **batch inference** on longer texts is available [here](https://colab.research.google.com/gist/pszemraj/6e961b08970f98479511bb1e17cdb4f0/batch-grammar-check-correct-demo.ipynb)\n",
|
| 15 |
+
"- [link to model card](https://huggingface.co/pszemraj/flan-t5-large-grammar-synthesis)\n",
|
| 16 |
+
"\n",
|
| 17 |
+
"\n",
|
| 18 |
+
"---\n",
|
| 19 |
+
"\n"
|
| 20 |
+
],
|
| 21 |
+
"metadata": {
|
| 22 |
+
"id": "LEpomcp9mMno"
|
| 23 |
+
}
|
| 24 |
+
},
|
| 25 |
+
{
|
| 26 |
+
"cell_type": "code",
|
| 27 |
+
"execution_count": null,
|
| 28 |
+
"metadata": {
|
| 29 |
+
"cellView": "form",
|
| 30 |
+
"id": "LrDWdEzv3LaX"
|
| 31 |
+
},
|
| 32 |
+
"outputs": [],
|
| 33 |
+
"source": [
|
| 34 |
+
"#@markdown add auto-Colab formatting with `IPython.display`\n",
|
| 35 |
+
"from IPython.display import HTML, display\n",
|
| 36 |
+
"# colab formatting\n",
|
| 37 |
+
"def set_css():\n",
|
| 38 |
+
" display(\n",
|
| 39 |
+
" HTML(\n",
|
| 40 |
+
" \"\"\"\n",
|
| 41 |
+
" <style>\n",
|
| 42 |
+
" pre {\n",
|
| 43 |
+
" white-space: pre-wrap;\n",
|
| 44 |
+
" }\n",
|
| 45 |
+
" </style>\n",
|
| 46 |
+
" \"\"\"\n",
|
| 47 |
+
" )\n",
|
| 48 |
+
" )\n",
|
| 49 |
+
"\n",
|
| 50 |
+
"get_ipython().events.register(\"pre_run_cell\", set_css)"
|
| 51 |
+
]
|
| 52 |
+
},
|
| 53 |
+
{
|
| 54 |
+
"cell_type": "code",
|
| 55 |
+
"execution_count": 1,
|
| 56 |
+
"metadata": {
|
| 57 |
+
"colab": {
|
| 58 |
+
"base_uri": "https://localhost:8080/"
|
| 59 |
+
},
|
| 60 |
+
"id": "lIYdn1woOS1n",
|
| 61 |
+
"outputId": "fba7842b-269d-4bfa-991c-714c8764281e"
|
| 62 |
+
},
|
| 63 |
+
"outputs": [
|
| 64 |
+
{
|
| 65 |
+
"output_type": "stream",
|
| 66 |
+
"name": "stdout",
|
| 67 |
+
"text": [
|
| 68 |
+
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m6.8/6.8 MB\u001b[0m \u001b[31m20.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
| 69 |
+
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m215.3/215.3 KB\u001b[0m \u001b[31m15.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
| 70 |
+
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m199.8/199.8 KB\u001b[0m \u001b[31m6.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
| 71 |
+
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.6/7.6 MB\u001b[0m \u001b[31m18.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
| 72 |
+
"\u001b[?25h"
|
| 73 |
+
]
|
| 74 |
+
}
|
| 75 |
+
],
|
| 76 |
+
"source": [
|
| 77 |
+
"pip install -U -q transformers accelerate"
|
| 78 |
+
]
|
| 79 |
+
},
|
| 80 |
+
{
|
| 81 |
+
"cell_type": "code",
|
| 82 |
+
"source": [
|
| 83 |
+
"from transformers import pipeline\n",
|
| 84 |
+
"\n",
|
| 85 |
+
"corrector = pipeline(\n",
|
| 86 |
+
" \"text2text-generation\",\n",
|
| 87 |
+
" \"pszemraj/flan-t5-large-grammar-synthesis\",\n",
|
| 88 |
+
")\n"
|
| 89 |
+
],
|
| 90 |
+
"metadata": {
|
| 91 |
+
"id": "8ZfUqTVJl8Zw",
|
| 92 |
+
"outputId": "991715c1-9a86-4c18-b9c7-d68dfedfd400",
|
| 93 |
+
"colab": {
|
| 94 |
+
"base_uri": "https://localhost:8080/",
|
| 95 |
+
"height": 209,
|
| 96 |
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"raw_text = \"Jamie 2the store yesturday to bye some food. I needd milk, bread, andafew otter things. The $$tore was reely crowed and I had a hard time finding everyting I needed. I finaly madeit t0 dacheck 0ut line and payed for my stuff.\" #@param {type:\"string\"}\n",
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| 258 |
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"\tJamie 2the store yesturday to bye some food. I needd milk, bread, andafew otter things. The $$tore was reely crowed and I had a hard time finding everyting I needed. I finaly madeit t0 dacheck 0ut line and payed for my stuff.\n"
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| 284 |
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| 285 |
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| 286 |
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"}"
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|
| 299 |
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|
| 300 |
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|
| 301 |
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|
| 302 |
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],
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{
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"text": [
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"Jamie went to the store yesterday to buy some food. I needed milk, bread, and a few other things. The store was very busy and I had a hard time finding everything I needed. I finally made it to the cashier and paid for my stuff. \n",
|
| 317 |
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"\n",
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| 318 |
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"\n",
|
| 319 |
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|
| 320 |
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|
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| 328 |
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"it's much faster on GPU + the inference parameters can be adjusted (less beams = faster, but worse quality).\n",
|
| 329 |
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"\n",
|
| 330 |
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"There is also now an [XL model here](https://huggingface.co/pszemraj/flan-t5-xl-grammar-synthesis)"
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