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corpus-oct-2024 / README.md
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---
license: cc-by-sa-4.0
size_categories:
- 10K<n<100K
task_categories:
- question-answering
dataset_info:
- config_name: angular
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path: godot/train-*
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path: langchain/train-*
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data_files:
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path: laravel/train-*
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data_files:
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path: yolo/train-*
---
# Dataset Card for FreshStack (Corpus)
[Homepage](https://fresh-stack.github.io) |
[Repository](https://github.com/fresh-stack/freshstack) |
[Paper](https://arxiv.org/abs/2504.13128)
FreshStack is a holistic framework to construct challenging IR/RAG evaluation datasets that focuses on search across niche and recent topics.
This dataset (October 2024) contains the query, nuggets, answers and nugget-level relevance judgments of 5 niche topics focused on software engineering and machine learning.
The queries and answers (accepted) are taken from Stack Overflow, GPT-4o generates the nuggets and labels the relevance between each nugget and a given document list.
This repository contains the corpus of GitHub chunked documents of five niche topics in freshstack. The queries, answers and nuggets can be found [here](https://huggingface.co/datasets/freshstack/queries-oct-2024).
## Dataset Structure
To access the data using HuggingFace `datasets`:
```
topic='langchain' # or any of the 5 topics
freshstack = datasets.load_dataset('freshstack/corpus-oct-2024', topic)
# train set
for data in freshstack['train']:
doc_id = data['_id']
doc_text = data['text']
```
## Dataset Statistics
The following table contains the number of documents (`#D`) and the number of GitHub repositories used (`#G`) in the FreshStack collection.
| Topic | Versions | Domain | Train | |
|:----:|:-----:|:-----:|:-----:|:------:|
| | | | **#D**| **#G** |
| langchain | - |Machine Learning | 49,514 | 10 |
| yolo | v7 & v8 | Computer Vision | 27,207 | 5 |
| laravel | 10 & 11 | Back-end Development | 52,351 | 9 |
| angualar | 16, 17 & 18 | Front-end Development| 117,288 | 4 |
| godot | 4 | Game Development | 25,482 | 6 |
## Dataset Licenses
The FreshStack datasets are provided under the CC-BY-SA 4.0 license.
> The original GitHub repositories used for constructing the corpus may contain non-permissive licenses; we advise the reader to check the licenses for each repository carefully.