fev
DeBERTa-v3-base-mnli-fever-anliDeBERTa-v3-large-mnli-fever-anli-ling-wanliDeBERTa-v3-base-mnli-fever-docnli-ling-2croberta-large-snli_mnli_fever_anli_R1_R2_R3-nliDeBERTa-v3-xsmall-mnli-fever-anli-ling-binaryroberta-large-snli_mnli_fever_anli_R1_R2_R3-nliOmega-Darker-Gaslight_The-Final-Forgotten-Fever-Dream-24B-i1-GGUFOmega-Darker-Gaslight_The-Final-Forgotten-Fever-Dream-24B-ultra-uncensored-heretic-v2-GGUF
Datasets
All datasets matching “fev”fev_datasets
Forecast evaluation datasets
This repository contains time series datasets that can be used for evaluation of univariate & multivariate forecasting models.
The main focus of this repository is on datasets that reflect real-world forecasting scenarios, such as those involving covariates, missing values, and other practical complexities.
The datasets follow a format that is compatible with the fev package.
Data format and usage
Each dataset satisfies the following… See the full description on the dataset page: https://huggingface.co/datasets/autogluon/fev_datasets.fev_datasets
FEV forecasting dataset collection — TsFile format
This repository is a conversion of autogluon/fev_datasets to Apache TsFile format, with 49 subsets. Each subset lives in its own directory, containing a .tsfile data file (large tables are automatically sharded into multiple .tsfile files) and a descriptive README.md.
This data was converted to a unified format by an external source and then to TsFile. License and attribution follow the original source; we claim no rights over… See the full description on the dataset page: https://huggingface.co/datasets/THULab/fev_datasets.nli_fever
Overview
The original dataset can be found here
while the Github repo is here.
This dataset has been proposed in Combining fact extraction and verification with neural semantic matching networks. This dataset has been created as a modification
of FEVER.
In the original FEVER setting, the input is a claim from Wikipedia and the expected output is a label.
However, this is different from the standard NLI formalization which is basically a pair-of-sequence to label problem.
To… See the full description on the dataset page: https://huggingface.co/datasets/pietrolesci/nli_fever.FEVER_test_top_250_only_w_correct-v2
FEVERHardNegatives
An MTEB dataset
Massive Text Embedding Benchmark
FEVER (Fact Extraction and VERification) consists of 185,445 claims generated by altering sentences extracted from Wikipedia and subsequently verified without knowledge of the sentence they were derived from. The hard negative version has been created by pooling the 250 top documents per query from BM25, e5-multilingual-large and e5-mistral-instruct.
Task category
t2t
Domains
Encyclopaedic, Written… See the full description on the dataset page: https://huggingface.co/datasets/mteb/FEVER_test_top_250_only_w_correct-v2.feval-sn47-rolloutsfever
Dataset Card for "fever"
Dataset Summary
With billions of individual pages on the web providing information on almost every conceivable topic, we should have
the ability to collect facts that answer almost every conceivable question. However, only a small fraction of this
information is contained in structured sources (Wikidata, Freebase, etc.) – we are therefore limited by our ability to
transform free-form text to structured knowledge. There is, however, another problem… See the full description on the dataset page: https://huggingface.co/datasets/fever/fever.