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README.md

@@ -17,31 +17,13 @@ task_categories:
 - text-generation
 - table-question-answering
 - summarization
-- conversational
+- text-retrieval
+- question-answering
+- text-classification
 size_categories:
 - 1K<n<10K
-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: 7581160
-    num_examples: 8655
-  download_size: 2685851
-  dataset_size: 7581160
 ---
-# Code des transports, non-instruct (11-12-2023)
+# Code des transports, non-instruct (2024-03-26)
 
 This project focuses on fine-tuning pre-trained language models to create efficient and accurate models for legal practice. 
 
@@ -64,6 +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
@@ -109,19 +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 transports, non-instruct (11-12-2023)},
-  howpublished = {\url{https://huggingface.co/datasets/louisbrulenaudet/code-transports}},
-  year =         {2023}
-}
-```
-
 ## Feedback
 
 If you have any feedback, please reach out at [louisbrulenaudet@icloud.com](mailto:louisbrulenaudet@icloud.com).