Datasets:
Tasks:
Text Generation
Modalities:
Text
Formats:
parquet
Languages:
English
Size:
< 1K
Tags:
shakespeare
License:
dataset_info: | |
features: | |
- name: text | |
dtype: string | |
splits: | |
- name: train | |
num_bytes: 4077942 | |
num_examples: 30 | |
- name: validation | |
num_bytes: 245785 | |
num_examples: 2 | |
- name: test | |
num_bytes: 506679 | |
num_examples: 4 | |
download_size: 3073023 | |
dataset_size: 4830406 | |
configs: | |
- config_name: default | |
data_files: | |
- split: train | |
path: data/train-* | |
- split: validation | |
path: data/validation-* | |
- split: test | |
path: data/test-* | |
task_categories: | |
- text-generation | |
language: | |
- en | |
tags: | |
- shakespeare | |
size_categories: | |
- n<1K | |
license: mit | |
pretty_name: shakespearefirstfolio | |
# shakespearefirstfolio | |
## About | |
🎭 Shakespeare's First Folio (a collection of 36 of Shakespeare's plays) as a Hugging Face dataset! | |
## Description | |
In 2015, Andrej Karpathy wrote a post called "The Unreasonable Effectiveness of Recurrent Neural Networks" in his blog. For the needs of this post, he created tinyshakespeare, a subset of Shakespeare's works in a single 40,000 lines file. Surprisingly, language models trained from scratch on this tiny dataset can produce samples that look very close to those written by Shakespeare himself. | |
Since then, tinyshakespeare has been the defacto dataset used as a first test while developing language models. Unfortunately, it has some problems: | |
1) It is a single file, which makes further processing difficult | |
2) It does not contain all of Shakespeare's works | |
3) It is not clear exactly what works and to what extend are included | |
This dataset tries to address these problems. It is ~4 times bigger than tinyshakespeare. | |
It was manually collected from [Folger Shakespeare Library](https://www.folger.edu/). | |
## Usage | |
import datasets | |
dataset = datasets.load_dataset("gvlassis/shakespearefirstfolio") |