\n\n\n
\n\n***Language Models for Question Generation (LMQG)*** is the official registry of
\"Generative Language Models for Paragraph-Level Question Generation, EMNLP 2022\" , which has proposed
QG-Bench , multilingual and multidomain question generation datasets and models.\nSee the official
GitHub for more information.\nThe QG models can be used with
`lmqg` library as below.\n\n
\n \n from lmqg import TransformersQG\n model = TransformersQG(language='en', model='lmqg/t5-large-squad-qg-ae')\n context = \"William Turner was an English painter who specialised \"\n \"in watercolour landscapes. He is often known as \"\n \"William Turner of Oxford or just Turner of Oxford to \"\n \"distinguish him from his contemporary, J. M. W. Turner. \"\n \"Many of Turner's paintings depicted the countryside \"\n \"around Oxford. One of his best known pictures is a \"\n \"view of the city of Oxford from Hinksey Hill.\"\n question_answer = model.generate_qa(context)\n print(question_answer)\n [\n ('Who was an English painter who specialised in watercolour landscapes?',\n 'William Turner'),\n (\"What was William Turner's nickname?\",\n 'William Turner of Oxford'),\n (\"What did many of Turner's paintings depict around Oxford?\",\n 'countryside'),\n (\"What is one of William Turner's best known paintings?\",\n 'a view of the city of Oxford')\n ]\n \n \n\nSee more information bellow.\n
\n\n\n","html":"
\n \n
\n\n
\n\n
Language Models for Question Generation (LMQG) is the official registry of \"Generative Language Models for Paragraph-Level Question Generation, EMNLP 2022\" , which has proposed QG-Bench , multilingual and multidomain question generation datasets and models.\nSee the official GitHub for more information.\nThe QG models can be used with lmqg library as below.
\n
\n from lmqg import TransformersQG\n model = TransformersQG(language='en', model='lmqg/t5-large-squad-qg-ae')\n context = \"William Turner was an English painter who specialised \"\n \"in watercolour landscapes. He is often known as \"\n \"William Turner of Oxford or just Turner of Oxford to \"\n \"distinguish him from his contemporary, J. M. W. Turner. \"\n \"Many of Turner's paintings depicted the countryside \"\n \"around Oxford. One of his best known pictures is a \"\n \"view of the city of Oxford from Hinksey Hill.\"\n question_answer = model.generate_qa(context)\n print(question_answer)\n [\n ('Who was an English painter who specialised in watercolour landscapes?',\n 'William Turner'),\n (\"What was William Turner's nickname?\",\n 'William Turner of Oxford'),\n (\"What did many of Turner's paintings depict around Oxford?\",\n 'countryside'),\n (\"What is one of William Turner's best known paintings?\",\n 'a view of the city of Oxford')\n ]\n \n \n\n
See more information bellow.
\n
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AI & ML interests
Language Model finetuning for Question Generation (LMQG)
Team members
3
Language Models for Question Generation (LMQG) is the official registry of "Generative Language Models for Paragraph-Level Question Generation, EMNLP 2022" , which has proposed QG-Bench , multilingual and multidomain question generation datasets and models.
See the official GitHub for more information.
The QG models can be used with lmqg library as below.
from lmqg import TransformersQG
model = TransformersQG(language='en', model='lmqg/t5-large-squad-qg-ae')
context = "William Turner was an English painter who specialised "
"in watercolour landscapes. He is often known as "
"William Turner of Oxford or just Turner of Oxford to "
"distinguish him from his contemporary, J. M. W. Turner. "
"Many of Turner's paintings depicted the countryside "
"around Oxford. One of his best known pictures is a "
"view of the city of Oxford from Hinksey Hill."
question_answer = model.generate_qa(context)
print(question_answer)
[
('Who was an English painter who specialised in watercolour landscapes?',
'William Turner'),
("What was William Turner's nickname?",
'William Turner of Oxford'),
("What did many of Turner's paintings depict around Oxford?",
'countryside'),
("What is one of William Turner's best known paintings?",
'a view of the city of Oxford')
]
See more information bellow.
models
181
lmqg/mt5-base-zhquad-qg-ae-trimmed-50000
Updated
Nov 14, 2023
•
1
lmqg/mt5-base-zhquad-qg-ae
Text Generation
•
Updated
Nov 13, 2023
•
2
Text Generation
•
Updated
Nov 13, 2023
•
2
lmqg/mt5-base-zhquad-qag-trimmed-50000
Updated
Nov 13, 2023
Text Generation
•
Updated
Nov 13, 2023
•
3
lmqg/mt5-base-zhquad-ae-trimmed-50000
Updated
Nov 12, 2023
•
1
Text Generation
•
Updated
Nov 12, 2023
•
2
lmqg/mt5-small-zhquad-qag-trimmed-50000
Updated
Nov 10, 2023
lmqg/mt5-small-zhquad-qag
Text Generation
•
Updated
Nov 10, 2023
•
4
Text Generation
•
Updated
Nov 10, 2023
•
7
datasets
27
lmqg/qa_harvesting_from_wikipedia_pseudo
Updated
Aug 24, 2024
•
37
lmqg/qa_harvesting_from_wikipedia
Updated
Aug 24, 2024
•
48
•
10
Updated
Aug 22, 2024
•
186
Updated
Nov 7, 2023
•
14
Updated
Nov 7, 2023
•
57
lmqg/qa_squadshifts_synthetic
Viewer
•
Updated
Jan 15, 2023
•
1.43M
•
1.65k
Updated
Dec 18, 2022
•
22
•
1
Updated
Dec 18, 2022
•
29
Viewer
•
Updated
Dec 18, 2022
•
15k
•
39
•
4
Viewer
•
Updated
Dec 18, 2022
•
29.1k
•
17
•
1