Create README.md

README.md

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+---
+license: openrail
+language:
+- fr
+tags:
+- french
+- philosophy
+- quebec
+size_categories:
+- 100K<n<1M
+---
+# Dataset Card for Dataset Name
+
+## Dataset Description
+
+### Dataset Summary
+
+This dataset contains all french philosophy that has been published on erudit.org. It has been generated using a Bs4 web parser that you can find in this repo: https://github.com/MFGiguere/french-philosophy-generator.
+
+### Supported Tasks and Leaderboards
+
+This dataset could be useful for this (non-exhaustive) set of tasks: detect if a text is philosophical or not, generate philosophical sentences, generate an abstract from an article, ...
+
+### Languages
+
+The database includes includes all journals where the main language is french but might include non-french sentences from quotes or special editions. 
+
+## Dataset Structure
+
+### Data Instances
+
+Each row of the databse is a sentence and each column is a text's metadata. 
+
+### Data Fields
+
+The data is structured as follow, which makes it possible to combine sentences into paragraphs, sections or whole texts. 
+features = {
+        "Journal": str,              #The name of the journal where the text was published
+        "Author": str,               #Required to be able to generate texts by author. 
+        "Year": str,                 #Will help form a sense of direction on a large scale.  
+        "Title": str,                #Can be useful for smaller dataset, but can be inferred with enough files. 
+        "section_rank": int,         #Abstract will be 0 and sections will start as 1. 
+        "par_rank": int,             #Abstract will be 0 and paragraphs will start as 1. 
+        "sent_rank": int,            #no of sentence in the paragraph
+        "text": str                  #Will be single sentence at a time. 
+        }
+
+## Additional Information
+
+### Contributions
+
+This dataset exists because of the Deepmay 2023 bootcamp instructors who gave us a solid instruction to language models and a friend at the Bootcamp that suggested me to host this dataset publicly on here!