datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
gpt3_nli
Overview
Original dataset available here. Debiased dataset generated with GPT-3.
Dataset curation
All string columns are stripped. Labels are encoded with the following mapping
{"entailment": 0, "neutral": 1, "contradiction": 2}
Code to create the dataset
import pandas as pd
from datasets import Dataset, ClassLabel, Value, Features
import json
# load data
with open("data/dataset.jsonl", "r") as fl:
df = pd.DataFrame([json.loads(line) for line in fl])… See the full description on the dataset page: https://huggingface.co/datasets/pietrolesci/gpt3_nli.GPT3-Token-EncoderFOLIO_by_paraphrased_gpt3.5spider-model-outputs-wo-gpt35RLAIF_summarization_preference_gpt35gpt-3.5_hanna_full_analyze_rategpt35_preference_rlaifQuestions_to_symptom_points_gpt3.5cots-gsm8k-generation-5-gpt3.5-turbogpt3.5_tweetsgpt-3.5-turbo-cosa-benchmark-resultsgpt3.5_hanna_rate_explain_96_prompts_llm_double_evalsst2-gpt3.5-turbo-poisoned-target-1-testsetgpt-3.5_SummEval_gpt2-vs-others_rate_explaingpt-3.5_SummEval_full_score_onlythesis-results-gpt3ftthesis-results-gpt3synthetic_tuples_gpt35_dedup_with_marginssynthetic_sts_gpt35_dedup_with_marginsgpt-3.5_SummEval_gpt2-vs-others_analyze_rategpt-3.5-turbo-evaluationGPT-3.5ProcessedDataset