pairwise
Datasets
All datasets matching “pairwise”synthetic-instruct-gptj-pairwisemsmarco-llm-reranking-pairwisepairwise_preferencesv2oasst1_pairwise_rlhf_reward
Dataset Card for "oasst1_pairwise_rlhf_reward"
OASST1 dataset preprocessed for reward modeling:
import pandas as pd
from datasets import load_dataset,concatenate_datasets, Dataset, DatasetDict
import numpy as np
dataset = load_dataset("OpenAssistant/oasst1")
df=concatenate_datasets(list(dataset.values())).to_pandas()
m2t=df.set_index("message_id")['text'].to_dict()
m2r=df.set_index("message_id")['role'].to_dict()
m2p=df.set_index('message_id')['parent_id'].to_dict()… See the full description on the dataset page: https://huggingface.co/datasets/tasksource/oasst1_pairwise_rlhf_reward.red_teaming_reward_modeling_pairwise
Dataset Card for "red_teaming_reward_modeling_pairwise"
More Information needed
fusion-pairwise-evals-test-time-scaling
Automatic pairwise preference evaluations for: Making, not taking, the Best-of-N
Content
This data contains pairwise automatic win-rate evaluations for the m-ArenaHard-v2.0 benchmark and it compares CommandA against gemini-2.5-pro in 2 settings:
Test-time scaling with Fusion : 5 samples are generated from CommandA, then fused with CommandA into one completion and compared to a single completion from gemini-2.5-pro
Test-time scaling with BoN : 5 samples are generated from… See the full description on the dataset page: https://huggingface.co/datasets/CohereLabs/fusion-pairwise-evals-test-time-scaling.