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@@ -6,13 +6,24 @@ size_categories:
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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 **48,069** 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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@@ -50,8 +61,9 @@ A list of prompts (see below) was then applied in order to build the input and t
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  # Splits
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- - train with 48,069 samples
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- - no valid and test splits in the original data
 
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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?