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README.md

@@ -1,52 +1,29 @@
 ---
+license: apache-2.0
 language:
 - fr
-license: apache-2.0
 multilinguality:
 - monolingual
-size_categories:
-- 1K<n<10K
-source_datasets:
-- original
-task_categories:
-- text-generation
-- table-question-answering
-- summarization
-- conversational
-pretty_name: Code des relations entre le public et l'administration
 tags:
 - finetuning
 - legal
 - french law
 - droit français
 - Code des relations entre le public et l'administration
-dataset_info:
-  features:
-  - name: instruction
-    dtype: string
-  - name: input
-    dtype: string
-  - name: output
-    dtype: string
-  - name: start
-    dtype: string
-  - name: expiration
-    dtype: string
-  - name: num
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 382784
-    num_examples: 471
-  download_size: 122527
-  dataset_size: 382784
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
+source_datasets:
+- original
+pretty_name: Code des relations entre le public et l'administration
+task_categories:
+- text-generation
+- table-question-answering
+- summarization
+- text-retrieval
+- question-answering
+- text-classification
+size_categories:
+- 1K<n<10K
 ---
-# Code des relations entre le public et l'administration, non-instruct (11-12-2023)
+# Code des relations entre le public et l'administration, non-instruct (2024-03-26)
 
 This project focuses on fine-tuning pre-trained language models to create efficient and accurate models for legal practice. 
 
@@ -69,6 +46,9 @@ This JSON file is a list of dictionaries, each dictionary contains the following
 - `instruction`: `string`, presenting the instruction linked to the element.
 - `input`: `string`, signifying the input details for the element.
 - `output`: `string`, indicating the output information for the element.
+- `start`: `string`, the date of entry into force of the article. 
+- `expiration`: `string`, the date of expiration of the article. 
+- `num`: `string`, the id of the article.
 
 We used the following list of instructions for generating the dataset:
 ```python
@@ -114,19 +94,6 @@ instructions = [
 ]
 ```
 
-## Citing this project
-
-If you use this code in your research, please use the following BibTeX entry.
-
-```BibTeX
-@misc{louisbrulenaudet2023,
-  author =       {Louis Brulé Naudet},
-  title =        {Code des relations entre le public et l'administration, non-instruct (11-12-2023)},
-  howpublished = {\url{https://huggingface.co/datasets/louisbrulenaudet/code-relations-public-administration}},
-  year =         {2023}
-}
-```
-
 ## Feedback
 
 If you have any feedback, please reach out at [[email protected]](mailto:[email protected]).