feat: updated README

README.md

@@ -1,15 +1,15 @@
 ---
 configs:
-- config_name: crag_task_1_and_2_subsample_1
-  data_files: crag_task_1_and_2/crag_task_1_and_2_dev_v4_subsample_cdf90925.jsonl.bz2
-- config_name: crag_task_1_and_2_subsample_2
-  data_files: crag_task_1_and_2/crag_task_1_and_2_dev_v4_subsample_2e617280.jsonl.bz2
-- config_name: crag_task_1_and_2_subsample_3
-  data_files: crag_task_1_and_2/crag_task_1_and_2_dev_v4_subsample_9bca9871.jsonl.bz2
-- config_name: crag_task_1_and_2_subsample_4
-  data_files: crag_task_1_and_2/crag_task_1_and_2_dev_v4_subsample_ff5aa423.jsonl.bz2
-- config_name: crag_task_1_and_2_subsample_5
-  data_files: crag_task_1_and_2/crag_task_1_and_2_dev_v4_subsample_3f4353ba.jsonl.bz2
+- config_name: crag_task_1_and_2_subset_1
+  data_files: crag_task_1_and_2/crag_task_1_and_2_dev_v4_subset_cdf90925.jsonl.bz2
+- config_name: crag_task_1_and_2_subset_2
+  data_files: crag_task_1_and_2/crag_task_1_and_2_dev_v4_subset_2e617280.jsonl.bz2
+- config_name: crag_task_1_and_2_subset_3
+  data_files: crag_task_1_and_2/crag_task_1_and_2_dev_v4_subset_9bca9871.jsonl.bz2
+- config_name: crag_task_1_and_2_subset_4
+  data_files: crag_task_1_and_2/crag_task_1_and_2_dev_v4_subset_ff5aa423.jsonl.bz2
+- config_name: crag_task_1_and_2_subset_5
+  data_files: crag_task_1_and_2/crag_task_1_and_2_dev_v4_subset_3f4353ba.jsonl.bz2
 license: cc-by-nc-4.0
 task_categories:
 - question-answering
@@ -26,6 +26,30 @@ pretty_name: CRA
 
 Datasets are taken from Facebook's [CRAG: Comprehensive RAG Benchmark](https://github.com/facebookresearch/CRAG), see their [arXiv paper](https://arxiv.org/abs/2406.04744) for details about the dataset construction.
 
+# CRAG Sampler
+
+We have added a simple Python tool for performing stratified sampling on CRAG data.
+
+## Installation
+
+### Local Development Install (Recommended)
+```bash
+git clone https://huggingface.co/Quivr/CRAG.git
+cd CRAG
+pip install -r requirements.txt  # Install dependencies
+pip install -e .  # Install package in development mode
+```
+
+## Quick Start
+
+### Running the example
+
+```bash
+python -m examples.basic_sampling
+```
+
+# CRAG dataset
+
 CRAG (Comprehensive RAG Benchmark) is a rich and comprehensive factual question answering benchmark designed to advance research in RAG. The public version of the dataset includes:
 - 2706 Question-Answer pairs
 - 5 domains: Finance, Sports, Music, Movie, and Open domain
@@ -34,7 +58,7 @@ CRAG (Comprehensive RAG Benchmark) is a rich and comprehensive factual question
 ![](figs/CRAG_table_2.png)
 
 The datasets `crag_task_1_and_2_dev_v4_subsample_*.json.bz2` have been created from the dataset [crag_task_1_and_2_dev_v4.jsonl.bz2](https://github.com/facebookresearch/CRAG/raw/refs/heads/main/data/crag_task_1_and_2_dev_v4.jsonl.bz2?download=) available on CRAG's GitHub repository. 
-For an easier handling and download of the dataset, we have used the script [crag_to_subsamples.py](https://huggingface.co/datasets/Quivr/crag/blob/main/crag_to_subsamples.py) to split the 2706 rows of the original file in 5 subsamples, following the procedure below: 
+For an easier handling and download of the dataset, we have used our CRAG sampler to split the 2706 rows of the original file in 5 subsamples, following the procedure below: 
 1. We have created a new label `answer_type`, classifying the answers in 3 categories:
       - `invalid` for any answer == "invalid question"
       - `no_answer` for any answer == "i don't know"