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Datasets:
recursal
/
Recursalberg

Tasks:
Text Generation
Fill-Mask
Modalities:
Text
Formats:
json
Sub-tasks:
language-modeling
masked-language-modeling
Languages:
English
Size:
10K - 100K
Tags:
Libraries:
Datasets
pandas
Croissant
License:
Dataset card Viewer Files Community
Recursalberg
File size: 4,988 Bytes 
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---
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
configs:
  - config_name: default
    data_files:
      - split: final
        path: jsonl/*
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 **~5.32B** (llama-2-7b-chat-tokenizer) / **~4.83B** (RWKV Tokenizer) from primarily English language.

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

### Dataset Sources

- **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.
```

## Recursal's Vision

> To make AI accessible to everyone, regardless of language, or economical status

This is the collective goal of the `RWKV Open Source foundation` and `Recursal AI`, the commercial entity who backs it.

We believe that AI should not be controlled by a select few individual organization. And that it should be made accessible regardless if you are rich or poor, or a native speaker of english.

### About RWKV

RWKV is an Open Source, non profit group, under the linux foundation. Focused on developing the RWKV AI architecture, in accordence to our vision.

The RWKV architecture scales efficiently and economically. As an RNN & Transformer hybrid, it is able to provide the performance similar to leading transformer models, while having the compute and energy efficiency of an RNN based architecture.

You can find out more about the project, and latest models, at the following

- [https://blog.rwkv.com](https://blog.rwkv.com)
- [https://wiki.rwkv.com](https://wiki.rwkv.com)


### About Recursal AI

Recursal AI, is the commercial entity built to provide support for RWKV model development and users, while providing commercial services via its public cloud, or private-cloud / on-premise offerings.

As part of our vision. Our commitment, is to ensure open source development and access to the best foundational AI models and datasets. 

The following dataset/models provided here, is part of that commitment.

You can find out more about recursal AI here

- [https://recursal.ai](https://recursal.ai)
- [https://blog.recursal.ai](https://blog.recursal.ai)

### 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.

For the post processed data under Recursal work, it's licensed as CC-BY-SA.

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{recursalberg,
  title         = {Recursalberg},
  author        = {KaraKaraWitch, recursal.ai},
  year          = {2024},
  howpublished  = {\url{https://huggingface.co/datasets/recursal/Recursalberg}},
}
```