Update README.md

README.md

@@ -33,37 +33,6 @@ This is reranking dataset built from 179 queris from [MSMARCO-V2 passages set](h
 Below are the data creation process:
 
 ```
-import sys
-from pyserini.search import get_topics, get_qrels
-from run_evaluation import THE_TOPICS, THE_INDEX
-from trec_eval import EvalFunction
-import json
-qrels = {}
-for data in ['dl21', 'dl22', 'dl23']:
-    qrels_file = get_qrels_file(THE_TOPICS[data])
-    with open(qrels_file, 'r') as f:
-        for line in f:
-            qid, _, docid, rel = line.strip().split()
-            if qid not in qrels:
-                qrels[qid] = {}
-            qrels[qid][docid] = int(rel)
-           
-# Save the combined qrels to a file
-output_file = './combined_qrels.txt'
-with open(output_file, 'w') as f:
-    for qid in sorted(qrels.keys()):
-        for docid, rel in qrels[qid].items():
-            f.write(f"{qid} 0 {docid} {rel}\n")
-
-
-# Concate the files
-combined_rank_results = []
-for data in ['dl21', 'dl22', 'dl23']:
-    with open(f'{data}_bm25_rank_results.json', 'r') as f:
-        rank_results = json.load(f)
-        print(f"len(rank_results): {len(rank_results)}")
-        combined_rank_results.extend(rank_results)
-
 # Multiple Random Sampling
 
 import copy
@@ -80,21 +49,4 @@ for item in combined_rank_results:
         replicate_rank_results.append(new_item)
 print(len(replicate_rank_results))
 
-# Push to huggingface
-
-from datasets import Dataset
-import pandas as pd
-from huggingface_hub import login
-df = pd.DataFrame(replicate_rank_results)
-dataset = Dataset.from_pandas(df)
-
-# Print dataset info
-print(f"Dataset size: {len(dataset)}")
-print(dataset)
-
-# Upload the dataset to Huggingface Hub
-dataset.push_to_hub(
-    "le723z/DeepRerank",  # Replace with your desired repository name
-    private=False,  # Set to True if you want a private dataset
-)
 ```