model update
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README.md
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@@ -53,14 +53,14 @@ This model is fine-tuned version of [facebook/bart-base](https://huggingface.co/
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[lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) (dataset_name: default) via [`lmqg`](https://github.com/asahi417/lm-question-generation).
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This model is fine-tuned without parameter search (default configuration is taken from [ERNIE-GEN](https://arxiv.org/abs/2001.11314)).
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Please cite our paper if you use the model ([
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```
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@inproceedings{ushio-etal-2022-generative,
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title = "{G}enerative {L}anguage {M}odels for {P}aragraph-{L}evel {Q}uestion {G}eneration
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author = "Ushio, Asahi and
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Alva-Manchego, Fernando
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Camacho-Collados, Jose",
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booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing",
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month = dec,
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- **Training data:** [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) (default)
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- **Online Demo:** [https://autoqg.net/](https://autoqg.net/)
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- **Repository:** [https://github.com/asahi417/lm-question-generation](https://github.com/asahi417/lm-question-generation)
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- **Paper:** [
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### Usage
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```python
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from
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question = pipe('<hl> Beyonce <hl> further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Records.')
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```
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The full configuration can be found at [fine-tuning config file](https://huggingface.co/lmqg/bart-base-squad-default/raw/main/trainer_config.json).
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## Citation
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@inproceedings{ushio-etal-2022-generative,
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title = "{G}enerative {L}anguage {M}odels for {P}aragraph-{L}evel {Q}uestion {G}eneration
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author = "Ushio, Asahi and
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Alva-Manchego, Fernando
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Camacho-Collados, Jose",
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booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing",
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month = dec,
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publisher = "Association for Computational Linguistics",
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}
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[lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) (dataset_name: default) via [`lmqg`](https://github.com/asahi417/lm-question-generation).
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This model is fine-tuned without parameter search (default configuration is taken from [ERNIE-GEN](https://arxiv.org/abs/2001.11314)).
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Please cite our paper if you use the model ([https://arxiv.org/abs/2210.03992](https://arxiv.org/abs/2210.03992)).
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```
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@inproceedings{ushio-etal-2022-generative,
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title = "{G}enerative {L}anguage {M}odels for {P}aragraph-{L}evel {Q}uestion {G}eneration",
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author = "Ushio, Asahi and
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Alva-Manchego, Fernando and
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Camacho-Collados, Jose",
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booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing",
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month = dec,
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- **Training data:** [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) (default)
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- **Online Demo:** [https://autoqg.net/](https://autoqg.net/)
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- **Repository:** [https://github.com/asahi417/lm-question-generation](https://github.com/asahi417/lm-question-generation)
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- **Paper:** [https://arxiv.org/abs/2210.03992](https://arxiv.org/abs/2210.03992)
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### Usage
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- With [`lmqg`](https://github.com/asahi417/lm-question-generation#lmqg-language-model-for-question-generation-)
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```python
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from lmqg import TransformersQG
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# initialize model
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model = TransformersQG(language='en', model='lmqg/bart-base-squad-default')
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# model prediction
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question = model.generate_q(list_context=["William Turner was an English painter who specialised in watercolour landscapes"], list_answer=["William Turner"])
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```
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- With `transformers`
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```python
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from transformers import pipeline
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# initialize model
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pipe = pipeline("text2text-generation", 'lmqg/bart-base-squad-default')
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# question generation
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question = pipe('<hl> Beyonce <hl> further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Records.')
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```
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The full configuration can be found at [fine-tuning config file](https://huggingface.co/lmqg/bart-base-squad-default/raw/main/trainer_config.json).
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## Citation
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```
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@inproceedings{ushio-etal-2022-generative,
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title = "{G}enerative {L}anguage {M}odels for {P}aragraph-{L}evel {Q}uestion {G}eneration",
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author = "Ushio, Asahi and
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Alva-Manchego, Fernando and
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Camacho-Collados, Jose",
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booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing",
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month = dec,
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publisher = "Association for Computational Linguistics",
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}
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```
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