Update README.md

README.md

@@ -6,15 +6,26 @@ size_categories:
 - 10K<n<100K
 task_categories:
 - text-generation
+tags:
+- DFP
+- french prompts
+annotations_creators:
+- found
+language_creators:
+- found
+multilinguality:
+- monolingual
+source_datasets:
+- french_book_reviews
 ---
 
 # french_book_reviews_fr_prompt_text_generation_from_title_base_sentiment_analysis
 
 ## Summary
 
-**french_book_reviews_fr_prompt_text_generation_from_title_base_sentiment_analysis** is a subset of the [**Dataset of French Prompts (DFP)**]().  
-It contains **48,069** rows that can be used for a text generation task.  
-The original data (without prompts) comes from the dataset [french_book_reviews](https://huggingface.co/datasets/Abirate/french_book_reviews).
+**french_book_reviews_fr_prompt_text_generation_from_title_base_sentiment_analysis** is a subset of the [**Dataset of French Prompts (DFP)**](https://huggingface.co/datasets/CATIE-AQ/DFP).   
+It contains **347,688** rows that can be used for a text generation task.  
+The original data (without prompts) comes from the dataset [french_book_reviews](https://huggingface.co/datasets/Abirate/french_book_reviews).  
 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.
 
 
@@ -110,8 +121,9 @@ targets = fbr['train']['reader_review'][i]
 
 
 # Splits
-- train with 48,069 samples
-- no valid and test splits in the original data
+- `train` with 347,688 samples
+- no `valid` split
+- no `test` split
 
 
 # How to use?
@@ -129,4 +141,4 @@ dataset = load_dataset("CATIE-AQ/french_book_reviews_fr_prompt_text_generation_f
 
 
 ## License
-CC0: Public Domain
+CC0: Public Domain