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Adventure
Daniel Defoe
Robinson Crusoe
"CHAPTER I. START IN LIFE\n\n\nI was born in the year 1632, in the city of York, of a good family,\n(...TRUNCATED)
Adventure
Mark Twain (Samuel Clemens)
The Adventures of Tom Sawyer
"CHAPTER I\n\n\n Tom! \n\nNo answer.\n\n TOM! \n\nNo answer.\n\n What s gone with that boy, I wonder(...TRUNCATED)
Adventure
Anthony Hope
The Mysterious Island
"CHAPTER I.\n\nTHE IMPOSSIBLE--INEVITABLE.\n\n\nIn the garden the question was settled without serio(...TRUNCATED)
Adventure
Robert Louis Stevenson
Treasure Island
"PART ONE--The Old Buccaneer\n\n\n\n\nI\nThe Old Sea-dog at the Admiral Benbow\n\n\nSquire Trelawney(...TRUNCATED)
Biographies
Edward Bellamy
The Life of James Watt
" Must you go up to that tiresome old college again to-night? \n\nPouting lips and delicate brows fr(...TRUNCATED)
Biographies
Herman Melville
The Life of Julius Caesar
"I am a rather elderly man. The nature of my avocations for the last\nthirty years has brought me in(...TRUNCATED)
Children's Books
Louisa May Alcott
Little Women
"PART 1\n\n\n\n\nCHAPTER ONE\nPLAYING PILGRIMS\n\n\n Christmas won t be Christmas without any presen(...TRUNCATED)
Children's Books
James M. Barrie
Peter Pan
"Chapter I.\nPETER BREAKS THROUGH\n\n\nAll children, except one, grow up. They soon know that they w(...TRUNCATED)
Children's Books
Lewis Carroll
The Adventures of Alice in Wonderland
"CHAPTER I.\nDown the Rabbit-Hole\n\n\nAlice was beginning to get very tired of sitting by her siste(...TRUNCATED)
Classics
Leo Tolstoy
Anna Karenina
"PART ONE\n\nChapter 1\n\n\nHappy families are all alike; every unhappy family is unhappy in its\now(...TRUNCATED)

Books

The books dataset consists of a diverse collection of books organized into 9 categories, it splitted to train, validation where the train contains 40 books, and the validation 9 books.

This dataset is cleaned well and designed to support various natural language processing (NLP) tasks, including text generation and masked language modeling.

Details

The dataset contains 4 columns:

  • title: The tilte of the book.
  • author: The author of the book.
  • category: The genre/category of the book.
  • EN: The whole content of the book, in english. it's very very clean.

Tasks:

  • Text Generation
  • Fill-Mask

Categories

The dataset is organized into the following categories:

  1. Adventure: 5 books.
  2. Biographies: 3 books.
  3. Children: 4 books.
  4. Classic: 7 books.
  5. Fantasy: 3 books.
  6. Historical: 6 books.
  7. Mystery: 7 books.
  8. Romance: 5 books.
  9. Science-Fiction: 9 books.

Splits

The dataset is splitted into the following splits:

  1. train: 40 books.
  2. validation: 9 books, 1 book from each category.

Usage

The books collection dataset is ideal for training and evaluating models for text generation and language modeling, it provides a broad range of genres and styles, making it a valuable resource for diverse NLP applications.

And here is an example of usage:

from datasets import load_dataset

books = load_dataset("IsmaelMousa/books", split="train")

print(books["EN"][0][:500])

output:

CHAPTER I. START IN LIFE


I was born in the year 1632, in the city of York, of a good family,
though not of that country, my father being a foreigner of Bremen, who
settled first at Hull. He got a good estate by merchandise, and leaving
off his trade, lived afterwards at York, from whence he had married my
mother, whose relations were named Robinson, a very good family in that
country, and from whom I was called Robinson Kreutznaer; but, by the
usual corruption of words in England, we are now c

Source

The books in this dataset are sourced from Project Gutenberg, an open-source digital library offering a vast collection of literary works.

License

The rights to the books are reserved by their respective authors. This dataset is provided under the Apache 2.0 license for both personal and commercial use, with proper attribution.

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