update README

README.md

@@ -121,4 +121,55 @@ configs:
   data_files:
   - split: train
     path: yolo/train-*
+license: cc-by-4.0
+task_categories:
+- sentence-similarity
+size_categories:
+- 10K<n<100K
 ---
+
+# Dataset Card for FreshStack (Corpus)
+
+## Dataset Description
+[Homepage](https://fresh-stack.github.io) | 
+[Repository](https://github.com/fresh-stack/freshstack) |
+[ArXiv](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, use_auth_token=True)
+
+# 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 repositories used (`#G`) in the FreshStack collection.
+
+| Topic | Domain | Train |        |
+|:----:|:-----:|:-----:|:------:|
+|            |     | **#D**| **#G** |
+|  langchain | Machine Learning     | 49,514  | 10 |
+|  yolo      | Computer Vision      | 27,207  | 5  |
+|  laravel   | Back-end Development | 52,351  | 9  |
+|  angualar  | Front-end Development| 117,288 | 4  |
+|  godot4    | 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.