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README.md
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pretty_name: tamil_stories
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---
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pretty_name: tamil_stories
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---
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# Summary
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`tamil_stories` is an open source dataset of instruct-style records generated by scraping publicly available short stories on the following websites.
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- [Siruvarmalar](https://www.siruvarmalar.com/)
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- [Tamilsurangam](https://www.tamilsurangam.in/)
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Apart from scraping and automated cleaning, the data was also tagged manually by a group of volunteers.
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This dataset created as part of [Aya Open Science Initiative](https://sites.google.com/cohere.com/aya-en/home) by Cohere For AI.
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This dataset can be used for any purpose, whether academic or commercial, under the terms of the [Apache 2.0](https://opensource.org/license/apache-2-0) License.
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Supported Tasks:
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- Training LLMs
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- Synthetic Data Generation
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- Data Augmentation
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- Question Answering
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Languages: Tamil Version: 1.0
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# Dataset Overview
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`tamil_stories` is a corpus of 1202 records generated by converting scraped stories into instruction-style. This Dataset can be used for the following tasks:
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- Given the story, generate the appropriate title for the story.
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- Given some prominent characters/words from the story along with the title, generate the complete story.
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# Intended Uses
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While immediately valuable for instruction fine tuning large language models, as a corpus of instruction prompts, this dataset also presents a valuable opportunity for synthetic data generation.
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For example, prompt-completions could be submitted as few-shot examples to a large open language model to generate new stories in a similar style.
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# Dataset
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## Load with Datasets
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To load this dataset with Datasets, you'll just need to install Datasets as `pip install datasets --upgrade` and then use the following code:
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```python
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from datasets import load_dataset
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ds = load_dataset('aitamilnadu/tamil_stories')
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```
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## Purpose of Collection
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Tamil is a low-resource language (inspite of having rich literature) where there are no instruct-style dataset to the best of my knowledge.
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This was created as a part of [Aya Open Science Initiative](https://sites.google.com/cohere.com/aya-en/home) from Cohere For AI to make sure Tamil is well represented in the space of AI/ML.
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Unlike other datasets that are limited to non-commercial use, this dataset can be used, modified, and extended for any purpose, including academic or commercial applications.
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## Sources
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The following are the websites from which the data is scraped.
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- [Siruvarmalar](https://www.siruvarmalar.com/)
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- [Tamilsurangam](https://www.tamilsurangam.in/)
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The scripts used for scraping and cleaning the data can be found here:
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[Tamilsurangam Webscraper](https://github.com/miluckshan-j/tamilsurangam-webscraper),
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[Siruvarmalar Webscraper](https://github.com/miluckshan-j/siruvarmalar-webscraper)
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[Dataset Creation](https://github.com/miluckshan-j/tamil-dataset-creation-tools)
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- The scraped data is carefully analysed making sure there are no missed words, spelling mistakes and the data is in Tamil only.
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- Words/characters are manually added to stories by volunteers.
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- Finally, converted the pre-processed data into instruct-style prompts and completions.
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## Templates
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For the creation of instruct-style prompts and completions from the scraped data, the following templates were used:
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1. Given the story, generate the appropriate title for the story.
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```python
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Prompt:
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கீழே கொடுக்கப்பட்டுள்ள கதைக்குப் பொருத்தமான தலைப்பைக் கொடு.
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கதை: {Story}
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Completion:
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கொடுக்கப்பட்டுள்ள கதைக்குப் பொருத்தமான தலைப்பு '{Title}' என்பதாகும்.
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```
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2. Given some prominent characters/words from the story along with the title, generate the complete story.
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```python
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Prompt:
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கீழே கொடுக்கப்பட்டுள்ள வார்த்தைகளையும் தலைப்பையும் பயன்படுத்தி சிறு கதை எழுதுக.
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வார்த்தைகள்: {Comma_Seperated_Words}
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தலைப்பு: {Title}
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Completion:
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{Story}
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```
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## Personal or Sensitive Data
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This dataset contains public information. To my knowledge, there are no private person’s personal identifiers or sensitive information.
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## Language
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Tamil
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# Known Limitations
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- The meanings used in the prompts/completions are chosen randomly based on the availability of complete sentences and this may reflect some bias by ignoring other meanings written by other scholars.
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# Contributors
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[miluckshan-j](https://github.com/miluckshan-j)
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[chezhian0599](https://github.com/chezhian0599)
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[AbinayaM02](https://github.com/AbinayaM02)
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[anitha67](https://github.com/anitha67)
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[vijiv11](https://github.com/vijiv11)
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[Lagstill](https://github.com/Lagstill)
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[Merlinecodes](https://github.com/Merlinecodes)
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