metadata

annotations_creators:
  - no-annotation
language_creators:
  - crowdsourced
license:
  - cc-by-sa-3.0
task_categories:
  - text-generation
  - fill-mask
task_ids:
  - language-modeling
  - masked-language-modeling
source_datasets:
  - original
language:
  - en
configs:
  - config_name: default
    data_files:
      - split: articles
        path: data/dev_files.jsonl
      - split: index
        path: data/dev_index.json
pretty_name: Devopedia

Dataset Card for Devopedia

Waifu to catch your attention.

Dataset Description

Devopedia is a ~1.15 M Tokens (llama-2-7b-chat-tokenizer) / ~999.32K Tokens (RWKV Tokenizer) scrape of Devopedia. It serves as a training resource for large language models and other NLP tasks. This card details the dataset's origin, content, and limitations.

Curated by: KaraKaraWitch
Funded by [optional]: Recursal.ai (I work there lol)
Shared by [optional]: KaraKaraWitch
Language(s) (NLP): English
License: cc-by-sa-4.0

Devopedia was created under time constraints for the release of EagleX v1, and may contain biases in selection.

Supported Tasks and Leaderboards

Primarily used for language modeling.

Languages

While the dataset is focused on English. Keep in mind there are other languages as well.

Processing and Filtering

We scraped the Devopedia for a list of articles. Writing them to a compiled file dev_index.json. Before scraping individual article for its page contents.

The article contents are then selected by sections. Each section is converted to Markdown. Including the appropriate title. No filtering was done over the dataset.

Data Instances

Refer to the following sample:

{
    "text": "# Hypothesis Testing and Types of Errors\n\n## Summary\n\n\nSuppose we want to study income of a population. We study a sample from the population and draw conclusions. The sample should represent the population for our study to be a reliable one.\n\n**Null hypothesis**  $(H_{0})$  is that sample represents population. Hypothesis testing provides us with framework to conclude if we have sufficient evidence to either accept or reject null hypothesis. \n\nPopulation characteristics are either assumed or drawn from third-party sources or judgements by subject matter experts. Population data and sample data are characterised by moments of its distribution (mean, variance, skewness and kurtosis). We test null hypothesis for equality of moments where population characteristic is available and conclude if sample represents population.\n\nFor example, given only mean income of population, <TRUNCATED...>"
}

Data Keys

Each json line is a dictionary with a text str.

Dataset Curators

KaraKaraWitch. (I typically hang out in PygmalionAI discord, sometimes EleutherAI. If something is wrong, @karakarawitch on discord.)

I'd be happy if you could spread the word and recommend this dataset.

Licensing Information

Devopedia lists their content as under CC-BY-SA.

Citation Information

@misc{Devopedia,
  title         = {Devopedia},
  author        = {KaraKaraWitch, recursal.ai},
  year          = {2023},
  howpublished  = {\url{https://huggingface.co/datasets/recursal/Devopedia}},
}