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Update README.md
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README.md
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- fr
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license: cc-by-nc-sa-4.0
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size_categories:
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-
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task_categories:
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- text-generation
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tags:
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## Summary
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**newsquadfr_fr_prompt_context_generation_with_answer_and_question** is a subset of the [**Dataset of French Prompts (DFP)**](https://huggingface.co/datasets/CATIE-AQ/DFP).
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It contains **
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The original data (without prompts) comes from the dataset [newsquadfr](https://huggingface.co/datasets/lincoln/newsquadfr) 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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- `valid` with
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- no `test` split
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- fr
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license: cc-by-nc-sa-4.0
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size_categories:
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- 100K<n<1M
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task_categories:
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- text-generation
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tags:
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## Summary
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**newsquadfr_fr_prompt_context_generation_with_answer_and_question** is a subset of the [**Dataset of French Prompts (DFP)**](https://huggingface.co/datasets/CATIE-AQ/DFP).
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It contains **101,040** rows that can be used for a context-generation (with answer)task.
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The original data (without prompts) comes from the dataset [newsquadfr](https://huggingface.co/datasets/lincoln/newsquadfr) 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 79,200 samples
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- `valid` with 21,800 samples
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- no `test` split
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