AlexWortega/openjev-data

openjev training data — everything except the benchmark part The mixture behind AlexWortega/openjev: a Qwen3.5 decoder trained as a 3-way NLI cross-encoder, where every downstream use — reranking, fact-checking, typed decisions, agent policies — is "each option becomes a hypothesis, score = P(entailment)". 2,346,729 rows. One row is one (premise, hypothesis) pair with a label. from datasets import load_dataset ds = load_dataset("AlexWortega/openjev-data"… See the full description on the dataset page: https://huggingface.co/datasets/AlexWortega/openjev-data.

<iframe src="https://silytics.si/embed/item/e59cb413-5156-4d60-b9ba-dc136dcf616e" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 16 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.