---
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: Recursalberg
---

# Dataset Card for Recursalberg

![](Recursalberg.png "Clara is a dedicated volunteer and digital archivist. Inspired by her ancestor, she is committed to making literature accessible to everyone. With a background in library science and a deep appreciation for cultural works, Clara spends her days digitizing rare books and proofreading texts. Her character design reflects her role as a guardian of knowledge, bridging the gap between the historical significance of printed books and the accessibility of digital formats. Clara's serene and knowledgeable presence makes her a relatable and inspiring figure for readers and volunteers alike.")

*Waifu to catch your attention.*

## Dataset Details

### Dataset Description

*Recursalberg* is a cleaned dataset of Project Gutenberg books. We downloaded all the publicly available Gutenberg books at the time and processed them.  
Filtering to a total amount of tokens of **~XYZB** (llama-2-7b-chat-tokenizer) / **~XYZ** (RWKV Tokenizer) from primarily English language.

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

### Dataset Sources [optional]

- **Source Data:** [gutenberg.org (see mirroring)](https://gutenberg.org/help/mirroring.html) (rclone download)

### Processing

We performed the following downloading and processing steps to prepare Retenberg.

1. Use gutenberg's mirror rclone to download to a folder.
2. Index gutenberg with `gutenberg_index.py` (Gather all items to find html documents.)
3. Process all book indexes that has a html version.
   - Remove Gutenberg pre html block, page numbers, html comments, table of contents
   - Convert sections to markdown
   - Clean new lines, standardize punctuations.
4. Save each html file into 1 jsonl file.


### Data Keys

```
text (str): the book's text. converted to markdown.
```

### Dataset Curators

KaraKaraWitch. (I typically hangout 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 for your use cases `:)`

### Licensing Information

Complicated. Refer to gutenberg's license [here](https://www.gutenberg.org/policy/license.html),

We haven't seen any in-copyrighted books in our dataset so far so we assume it's safe for usage, unless otherwise.

### Citation Information

```
@ONLINE{recursalberg,
  title         = {Recursalberg},
  author        = {KaraKaraWitch, recursal.ai},
  year          = {2023},
  howpublished  = {\url{TBD}},
}
```