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README.md
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- 10K<n<100K
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task_categories:
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- text-generation
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---
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# piaf_fr_prompt_question_generation_with_context
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## Summary
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**piaf_fr_prompt_question_generation_with_context** is a subset of the [**Dataset of French Prompts (DFP)**]().
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It contains **
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The original data (without prompts) comes from the dataset [PIAF](https://huggingface.co/datasets/etalab-ia/piaf) and was augmented by questions in SQUAD 2.0 format in the [FrenchQA]( https://huggingface.co/datasets/CATIE-AQ/frenchQA) dataset.
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A list of prompts (see below) was then applied in order to build the input and target columns and thus obtain the same format as the [xP3](https://huggingface.co/datasets/bigscience/xP3) dataset by Muennighoff et al.
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# Splits
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- train with
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- no valid
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# How to use?
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- 10K<n<100K
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task_categories:
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- text-generation
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tags:
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- DFP
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- french prompts
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annotations_creators:
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- found
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language_creators:
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- found
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multilinguality:
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- monolingual
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source_datasets:
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- piaf
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---
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# piaf_fr_prompt_question_generation_with_context
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## Summary
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**piaf_fr_prompt_question_generation_with_context** is a subset of the [**Dataset of French Prompts (DFP)**](https://huggingface.co/datasets/CATIE-AQ/DFP).
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It contains **442,752** rows that can be used for a question-generation (with context) task.
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The original data (without prompts) comes from the dataset [PIAF](https://huggingface.co/datasets/etalab-ia/piaf) and was augmented by questions in SQUAD 2.0 format in the [FrenchQA]( https://huggingface.co/datasets/CATIE-AQ/frenchQA) dataset.
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A list of prompts (see below) was then applied in order to build the input and target columns and thus obtain the same format as the [xP3](https://huggingface.co/datasets/bigscience/xP3) dataset by Muennighoff et al.
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# Splits
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- `train` with 442,752 samples
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- no `valid` split
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- no `test` split
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# How to use?
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