Transformers
PyTorch
JAX
Safetensors
t5
text2text-generation
question-generation
text-generation-inference
Instructions to use p208p2002/t5-squad-nqg-hl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use p208p2002/t5-squad-nqg-hl with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("p208p2002/t5-squad-nqg-hl") model = AutoModelForSeq2SeqLM.from_pretrained("p208p2002/t5-squad-nqg-hl", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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# Transformer QG on SQuAD
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C' = [c1, c2, ..., [HL], a1, ..., a|A|, [HL], ..., c|C|]
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> Proposed by [Ying-Hong Chan & Yao-Chung Fan. (2019). A Re-current BERT-based Model for Question Generation.](https://www.aclweb.org/anthology/D19-5821/)
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More detail: [p208p2002/Transformer-QG-on-SQuAD](https://github.com/p208p2002/Transformer-QG-on-SQuAD)
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##
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## Data setting
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We report two dataset setting as Follow
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### SQuAD
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- train: 87599
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- validation: 10570
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> [SQuAD: 100,000+ Questions for Machine Comprehension of Text](https://arxiv.org/abs/1606.05250)
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# Transformer QG on SQuAD
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HLQG is Proposed by [Ying-Hong Chan & Yao-Chung Fan. (2019). A Re-current BERT-based Model for Question Generation.](https://www.aclweb.org/anthology/D19-5821/)
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**This is a Reproduce Version**
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More detail: [p208p2002/Transformer-QG-on-SQuAD](https://github.com/p208p2002/Transformer-QG-on-SQuAD)
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## Usage
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### Input Format
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```
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C' = [c1, c2, ..., [HL], a1, ..., a|A|, [HL], ..., c|C|]
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```
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### Input Example
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```
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Harry Potter is a series of seven fantasy novels written by British author, [HL]J. K. Rowling[HL].
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```
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> # Who wrote Harry Potter?
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## Data setting
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We report two dataset setting as Follow
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### SQuAD
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- train: 87599\t
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- validation: 10570
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> [SQuAD: 100,000+ Questions for Machine Comprehension of Text](https://arxiv.org/abs/1606.05250)
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