metadata

annotations_creators:
  - no-annotation
language_creators:
  - crowdsourced
license:
  - cc-by-sa-4.0
task_categories:
  - text-generation
  - fill-mask
task_ids:
  - language-modeling
  - masked-language-modeling
source_datasets:
  - original
language:
  - en
pretty_name: Lecture Gratuits

Dataset Card for LectureGratuits

Waifu to catch your attention.

Dataset Details

Dataset Description

LectureGratuits is a cleaned dataset of Ebooks Gratuits books. We downloaded all the publicly available ebooks books at the time and processed them.
Filtering to a total amount of tokens of ~X.YYB (llama-2-7b-chat-tokenizer) / ~X.YYB (RWKV Tokenizer) from primarily English language.

Curated by: Darok
Funded by [optional]: Recursal.ai
Shared by [optional]: KaraKaraWitch
Language(s) (NLP): English
License: Public domain? (TBC)

Dataset Sources [optional]

Source Data: ebooksgratuits.com (rclone download)

Processing

KaraKaraWitch doesn't have specifics on how it's processed. We have postiluated the following workflow / processing:

Get the higher ID
Enumerate and download all the epub files: https://www.ebooksgratuits.com/newsendbook.php?id=<ID>&format=epub
Put them in a folder called books
extract content to each json file in output folder. (See filtering steps in extract-text.py)
Combine into a single file.

Data Keys

text (str): The book's text. Converted to markdown.
meta (dict): A dictionary of metadata with the following keys:
  - title
  - author
  - publisher

Dataset Curators

This dataset was mainly Darok's work. I (KaraKaraWitch) only assisted them with questions and the writing of the dataset card.

Licensing Information

Public domain? (TBC)

Recursal Waifus (The banner image) are licensed under CC-BY-SA. They do not represent the related websites in any official capacity unless otherwise or announced by the website. You may use them as a banner image. However, you must always link back to the dataset.

Citation Information

@ONLINE{lecturegratuits,
  title         = {LectureGratuits},
  author        = {Darok, KaraKaraWitch, recursal.ai},
  year          = {2024},
  howpublished  = {\url{https://huggingface.co/datasets/recursal/Recursalberg}},
}