Baselight

Evol Codealpaca V1

An Innovative Augmentation Strategy for NLP

@kaggle.thedevastator_evol_codealpaca_v1_chinese_english_conversion

Loading...
Loading...

About this Dataset

Evol Codealpaca V1


Evol Codealpaca V1

An Innovative Augmentation Strategy for NLP

By Huggingface Hub [source]


About this dataset

This dataset, developed by Evol-Codealpaca, offers an innovative way to expand natural language processing capabilities through Chinese-English code conversion augmentation. Train.csv is a comprehensive collection of instructions and corresponding conversions from English to Chinese using a median sequence length of 471. With this data, researchers can explore new ideas for improving the accuracy of machine translation between these two languages by exploring different language techniques and strategies that generate accurate output. Evol-Codealpaca's dataset provides an innovative resource for enhancing machine translation applications and deepening our understanding of automated converstion processes between English and Chinese processing

More Datasets

For more datasets, click here.

Featured Notebooks

  • 🚨 Your notebook can be here! 🚨!

How to use the dataset

Step 1: Download the datasettrain.csv from Kaggle and save it onto your local computer, where you can easily access it with a text editor.

Step 2: Use a text editor to open train.csv. You will notice two columns in this dataset, labeled ‘instruction’ and ‘output’.

Step 3: The column labeled ‘instruction’ contains the original English instructions which are to be correspondingly translated in the ‘output’ column into Chinese instructions as produced by Evol-Codealpaca using their language augmentation technique. This technology allows realistic English translations of instructions given an impressive median sequence length of 471 characters for corresponding Chinese instructions in the output column of train.csv
step 4: With these converted illustrate translations, researchers can now explore a range of applications for natural language processing and incorporate them into various projects gaining valuable insights on how Evol-Codealpaca's advanced language augmentation method works effectively for code conversion processes between English and Chinese languages.

Research Ideas

  • Developing a model for automatically translating English instructions into Chinese.
  • Training neural networks on Evol-Codealpaca’s augmentation techniques to improve the accuracy of large language translation projects.
  • Incorporating Evol-Codealpaca’s approach into artificial intelligence (AI) programs for natural language processing and other language-related applications

Acknowledgements

If you use this dataset in your research, please credit the original authors.
Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication
No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: train.csv

Column name Description
instruction This column contains the original English instructions that are used as input. (String)
output This column contains the converted Chinese instructions that are generated as output of this augmentation process. (String)

Acknowledgements

If you use this dataset in your research, please credit the original authors.
If you use this dataset in your research, please credit Huggingface Hub.

Tables

Train

@kaggle.thedevastator_evol_codealpaca_v1_chinese_english_conversion.train
  • 129.14 MB
  • 111272 rows
  • 2 columns
Loading...

CREATE TABLE train (
  "instruction" VARCHAR,
  "output" VARCHAR
);

Share link

Anyone who has the link will be able to view this.