2166 lines
85 KiB
Plaintext
2166 lines
85 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "W8-j-5oV0o46",
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"outputId": "2b90f9b1-acb4-45e2-9a2f-2818e6fe03b8"
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
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"Requirement already satisfied: torch in /usr/local/lib/python3.10/dist-packages (2.0.1+cu118)\n",
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"Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from torch) (3.12.0)\n",
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"Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
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"Collecting transformers\n",
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" Downloading transformers-4.30.2-py3-none-any.whl (7.2 MB)\n",
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" Downloading tokenizers-0.13.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (7.8 MB)\n",
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"Installing collected packages: tokenizers, safetensors, huggingface-hub, transformers\n",
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"Successfully installed huggingface-hub-0.15.1 safetensors-0.3.1 tokenizers-0.13.3 transformers-4.30.2\n",
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"Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
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"Collecting datasets\n",
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" Downloading datasets-2.13.0-py3-none-any.whl (485 kB)\n",
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"Collecting xxhash (from datasets)\n",
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" Downloading xxhash-3.2.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (212 kB)\n",
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" Downloading aiohttp-3.8.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.0 MB)\n",
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"Installing collected packages: xxhash, multidict, frozenlist, dill, async-timeout, yarl, multiprocess, aiosignal, aiohttp, datasets\n",
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"Successfully installed aiohttp-3.8.4 aiosignal-1.3.1 async-timeout-4.0.2 datasets-2.13.0 dill-0.3.6 frozenlist-1.3.3 multidict-6.0.4 multiprocess-0.70.14 xxhash-3.2.0 yarl-1.9.2\n"
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]
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}
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],
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"source": [
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"!pip install torch\n",
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"!pip install transformers\n",
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"!pip install datasets"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "O6aa5mpE0s6H",
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"outputId": "43b0e006-1678-41f1-9b40-6964f9127a74"
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Cloning into 'challenging-america-word-gap-prediction'...\n",
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"remote: Wymienianie obiektów: 27, gotowe.\u001b[K\n",
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"remote: Zliczanie obiektów: 100% (27/27), gotowe.\u001b[K\n",
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"remote: Kompresowanie obiektów: 100% (23/23), gotowe.\u001b[K\n",
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"remote: Razem 27 (delty 2), użyte ponownie 17 (delty 0), paczki użyte ponownie 0\u001b[K\n",
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"Receiving objects: 100% (27/27), 278.33 MiB | 21.80 MiB/s, done.\n",
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"Resolving deltas: 100% (2/2), done.\n"
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]
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}
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],
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"source": [
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"!git clone --single-branch git://gonito.net/challenging-america-word-gap-prediction -b master"
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]
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},
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{
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"cell_type": "code",
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||
"execution_count": 4,
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||
"metadata": {
|
||
"id": "uHkXCRs-0iSr"
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},
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"outputs": [],
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||
"source": [
|
||
"import torch\n",
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"import sys\n",
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||
"from transformers import GPT2Tokenizer, GPT2LMHeadModel\n"
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]
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},
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{
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"cell_type": "code",
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||
"execution_count": 5,
|
||
"metadata": {
|
||
"id": "HyKM4zn41YvQ"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"import torch\n",
|
||
"import sys\n",
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"from transformers import GPT2Tokenizer, GPT2LMHeadModel\n",
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"\n",
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"import lzma\n",
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||
"from itertools import islice\n",
|
||
"import regex as re\n",
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"import math\n",
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"import sys\n",
|
||
"from torchtext.vocab import build_vocab_from_iterator\n",
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||
"from torch import nn\n",
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||
"from torch.utils.data import IterableDataset\n",
|
||
"import itertools"
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||
]
|
||
},
|
||
{
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||
"cell_type": "code",
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||
"execution_count": 6,
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||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/"
|
||
},
|
||
"id": "-k8RhlmI06mQ",
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||
"outputId": "39d0fc5d-c6ea-4f4b-e75e-cbe199bd175a"
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"/content/challenging-america-word-gap-prediction\n"
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]
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||
}
|
||
],
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||
"source": [
|
||
"%cd /content/challenging-america-word-gap-prediction"
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]
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},
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{
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"cell_type": "code",
|
||
"execution_count": 7,
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||
"metadata": {
|
||
"id": "PCA7Ank2dnwM"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"\n",
|
||
"device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 8,
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"metadata": {
|
||
"colab": {
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||
"base_uri": "https://localhost:8080/",
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"height": 177,
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||
"referenced_widgets": [
|
||
"679cc8100859428eaed49abdb40f93d1",
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||
"c4a853a74ab44187a321bba0e0c242a9",
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||
"2196c28d51fc4e7da12de6b95f915c83",
|
||
"eab433dc0a754595be140a7bebac7d53",
|
||
"2716e1a313324f17a613d453496da711",
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