Assalamualaikum Sahabat Whitecyber semua …. 🙂
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Kali ini Whitecyber Team akan berbagi Project kecil sample dalam pembuatan Chat GPT yang bisa kita buat sendiri menggunakan Python. Memang untuk Chat GPT sendiri membutuhkan DATABASE yang sangat besar, dengan kekuatan RAM, dan PROCESSOR yang sangat besar, Tentunya itu tidak kita kerjakan. Namun kami akan share Tips dan Logika cara membuat Chat GPT sendiri berbasis 1 tabel. Kami catat disini supaya tidak hilang, dengan sumber disini.
Kami menggunakan Teknologi GOOGLE COLLABS untuk membangun code ini. Dibutuhkan 500 MEGA hanya untuk mengakses 1 buah tabel. Jadi terbayang kan, seberapa besar Source Computer yang harus kita sendiakan untuk membangun Chat GPT kita sendiri bila ingin bersaing dengan Chat GPT yang aslinya.
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Yuk kita simak tahap-tahapnya adalah sebagai berikut :
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!pip install -q transformers==4.4.2
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Building wheel for sacremoses (setup.py) ... done
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In [2]:
import torch torch.__version__
Out[2]:
'1.13.0+cu116'
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In [3]:
!pip install torch-scatter -f https://pytorch-geometric.com/whl/torch-1.8.0+cu101.html
Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/
Looking in links: https://pytorch-geometric.com/whl/torch-1.8.0+cu101.html
Collecting torch-scatter
Downloading torch_scatter-2.1.0.tar.gz (106 kB)
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Building wheels for collected packages: torch-scatter
Building wheel for torch-scatter (setup.py) ... done
Created wheel for torch-scatter: filename=torch_scatter-2.1.0-cp38-cp38-linux_x86_64.whl size=477429 sha256=03e935c7a6a0484b6aba91736600ada76361332852ebe414ae6c1c1fec021451
Stored in directory: /root/.cache/pip/wheels/41/7f/4f/cf072bea3b6efe4561de2db3603ebbd8718c134c24caab8281
Successfully built torch-scatter
Installing collected packages: torch-scatter
Successfully installed torch-scatter-2.1.0
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In [4]:
from transformers import pipeline import pandas as pd
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In [5]:
tqa = pipeline(task=”table-question-answering”,model=”google/tapas-base-finetuned-wtq”)
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In [8]:
table=pd.read_csv(“data.csv”)
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In [9]:
table = table.astype(str)
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In [10]:
table
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Out[10]:
| Pos | Player | Team | Span | Innings | Runs | Highest Score | Average | Strike Rate | |
|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | Sachin Tendulkar | India | 1989-2012 | 452 | 18426 | 200 | 44.83 | 86.23 |
| 1 | 2 | Kumar Sangakkara | Sri Lanka | 2000-2015 | 380 | 14234 | 169 | 41.98 | 78.86 |
| 2 | 3 | Ricky Ponting | Australia | 1995-2012 | 365 | 13704 | 164 | 42.03 | 80.39 |
| 3 | 4 | Sanath Jayasuriya | Sri Lanka | 1989-2011 | 433 | 13430 | 189 | 32.36 | 91.2 |
| 4 | 5 | Mahela Jayawardene | Sri Lanka | 1998-2015 | 418 | 12650 | 144 | 33.37 | 78.96 |
| 5 | 6 | Virat Kohli | India | 2008-2020 | 236 | 11867 | 183 | 59.85 | 93.39 |
| 6 | 7 | Inzamam-ul-Haq | Pakistan | 1991-2007 | 350 | 11739 | 137 | 39.52 | 74.24 |
| 7 | 8 | Jacques Kallis | South Africa | 1996-2014 | 314 | 11579 | 139 | 44.36 | 72.89 |
| 8 | 9 | Saurav Ganguly | India | 1992-2007 | 300 | 11363 | 183 | 41.02 | 73.7 |
| 9 | 10 | Rahul Dravid | India | 1996-2011 | 318 | 10889 | 153 | 39.16 | 71.24 |
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In [11]:
query = “Who has scored the highest runs?”print(tqa(table=table,query=query)[“answer”])
Sachin Tendulkar . Bagaimana code pemprogramannya ? nie kami share disini. . CODE PROGRAM .
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"Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
"Looking in links: https://pytorch-geometric.com/whl/torch-1.8.0+cu101.html\n",
"Collecting torch-scatter\n",
" Downloading torch_scatter-2.1.0.tar.gz (106 kB)\n",
"\u001b[K |████████████████████████████████| 106 kB 5.2 MB/s \n",
"\u001b[?25hBuilding wheels for collected packages: torch-scatter\n",
" Building wheel for torch-scatter (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
" Created wheel for torch-scatter: filename=torch_scatter-2.1.0-cp38-cp38-linux_x86_64.whl size=477429 sha256=03e935c7a6a0484b6aba91736600ada76361332852ebe414ae6c1c1fec021451\n",
" Stored in directory: /root/.cache/pip/wheels/41/7f/4f/cf072bea3b6efe4561de2db3603ebbd8718c134c24caab8281\n",
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" Pos Player Team Span Innings Runs \\\n",
"0 1 Sachin Tendulkar India 1989-2012 452 18426 \n",
"1 2 Kumar Sangakkara Sri Lanka 2000-2015 380 14234 \n",
"2 3 Ricky Ponting Australia 1995-2012 365 13704 \n",
"3 4 Sanath Jayasuriya Sri Lanka 1989-2011 433 13430 \n",
"4 5 Mahela Jayawardene Sri Lanka 1998-2015 418 12650 \n",
"5 6 Virat Kohli India 2008-2020 236 11867 \n",
"6 7 Inzamam-ul-Haq Pakistan 1991-2007 350 11739 \n",
"7 8 Jacques Kallis South Africa 1996-2014 314 11579 \n",
"8 9 Saurav Ganguly India 1992-2007 300 11363 \n",
"9 10 Rahul Dravid India 1996-2011 318 10889 \n",
"\n",
" Highest Score Average Strike Rate \n",
"0 200 44.83 86.23 \n",
"1 169 41.98 78.86 \n",
"2 164 42.03 80.39 \n",
"3 189 32.36 91.2 \n",
"4 144 33.37 78.96 \n",
"5 183 59.85 93.39 \n",
"6 137 39.52 74.24 \n",
"7 139 44.36 72.89 \n",
"8 183 41.02 73.7 \n",
"9 153 39.16 71.24 "
],
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" <td>Sachin Tendulkar</td>\n",
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" <td>1989-2012</td>\n",
" <td>452</td>\n",
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" <td>1995-2012</td>\n",
" <td>365</td>\n",
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" <td>2008-2020</td>\n",
" <td>236</td>\n",
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" <td>Inzamam-ul-Haq</td>\n",
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" <td>1991-2007</td>\n",
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" <td>1996-2014</td>\n",
" <td>314</td>\n",
" <td>11579</td>\n",
" <td>139</td>\n",
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" <td>72.89</td>\n",
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" <th>8</th>\n",
" <td>9</td>\n",
" <td>Saurav Ganguly</td>\n",
" <td>India</td>\n",
" <td>1992-2007</td>\n",
" <td>300</td>\n",
" <td>11363</td>\n",
" <td>183</td>\n",
" <td>41.02</td>\n",
" <td>73.7</td>\n",
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" <th>9</th>\n",
" <td>10</td>\n",
" <td>Rahul Dravid</td>\n",
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" <td>1996-2011</td>\n",
" <td>318</td>\n",
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},
"metadata": {},
"execution_count": 10
}
]
},
{
"cell_type": "code",
"source": [
"query = \"Who has scored the highest runs?\"\n",
"print(tqa(table=table,query=query)[\"answer\"])"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "VsQ6vnWexIXW",
"outputId": "c9a78b2f-1cdf-4774-b936-e03d82a42cc7"
},
"execution_count": 11,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Sachin Tendulkar\n"
]
}
]
},
{
"cell_type": "code",
"source": [],
"metadata": {
"id": "3goEexBYu0_I"
},
"execution_count": null,
"outputs": []
}
]
}.
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