pxyyy/NuminaMath-CoT-smp20k-removed-top500-by-logix-for-MATH-Correct-2k

import numpy as np import torch from tqdm import tqdm from datasets import load_dataset, DatasetDict, Dataset import datasets def get_top_n_docs(scores, n): """Return top-n document indices for a query, ignoring negative scores.""" valid_docs = np.where(scores >= 0)[0] # Filter out negative scores sorted_indices = np.argsort(-scores[valid_docs]) # Descending order top_n_indices = valid_docs[sorted_indices][:n] # Take top n return set(top_n_indices) def… See the full description on the dataset page: https://huggingface.co/datasets/pxyyy/NuminaMath-CoT-smp20k-removed-top500-by-logix-for-MATH-Correct-2k.