size_categories:100K<n<1M format:parquet modality:text library:datasets library:pandas library:mlcroissant library:polars region:us
---
dataset_info:
  features:
  - name: anchor
    dtype: string
  - name: positive
    dtype: string
  - name: negative
    dtype: string
  splits:
  - name: train
    num_bytes: 143845823
    num_examples: 317521
  - name: test
    num_bytes: 61833745
    num_examples: 136081
  download_size: 51750220
  dataset_size: 205679568
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: test
    path: data/test-*
---
# Description

This dataset has been built from the MBPP dataset for fine tuning dense retrieval models. The dataset was created by using the first 70% points from the MBPP dataset. We created triplets corresponding to all negatives for a positive pair. Hence there are n * (n - 1) triplets for n pairs(since we have n-1 negative examples for every anchor-positive pair). Using a random seed of 10, we split these triplets into train and test subsest with a 70:30 ratio.

## Fields

1. `anchor` - The question corresponding to a code snippet
2. `positive` - The ground truth answer for the corresponding question
3. `negative` - Any other code snippet from the dataset not corresponding to the question
