Update README.md

README.md

@@ -6,14 +6,24 @@ size_categories:
 - 10K<n<100K
 task_categories:
 - text-generation
+tags:
+- DFP
+- french prompts
+annotations_creators:
+- found
+language_creators:
+- found
+multilinguality:
+- monolingual
+source_datasets:
+- piaf
 ---
 
 # piaf_fr_prompt_context_generation_with_answer_and_question
 ## Summary
 
-**piaf_fr_prompt_context_generation_with_answer_and_question** is a subset of the [**Dataset of French Prompts (DFP)**]().  
-It contains **48,069** rows that can be used for a context-generation (with answer and question)
-task.  
+**piaf_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).  
+It contains **442,752** rows that can be used for a context-generation (with answer and question) task.  
 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.
 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.
 
@@ -48,8 +58,9 @@ A list of prompts (see below) was then applied in order to build the input and t
 
 
 # Splits
-- train with 48,069 samples
-- no valid and test splits in the original data
+- `train` with 442,752 samples
+- no `valid` split
+- no `test` split
 
 
 # How to use?