datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
gspc-affect
GSPC — affect bank (AffectBench)
Council of AI measurement bank. Measurement, not certification.
Bank. Frozen split. Live n is the matching axis on GET https://councilof.ai/api/gspc, not a Hub score. Not a certificate. Art 50 (EUR-Lex): 2 August 2026 live; marking grace 2 December 2026.
Live measurement. This bank stands behind the affect row of the live GSPC board: GET https://councilof.ai/api/gspc?axis=affect (family, kind, status and n are on that row, never typed here; the… See the full description on the dataset page: https://huggingface.co/datasets/csoai/gspc-affect.llm-affect-lab
LLM Affect Lab
This dataset contains the API-level results for LLM Affect Lab, a study of functional affect signatures in language model behavior.
Functional Affect Score (FAS) is a 0-1 behavioral proxy. It combines generated-token confidence, enthusiastic language, consistency across repeated samples, forced self-report computed from digit top-logprob probabilities, and length control. The goal is not to claim that models feel emotions; the goal is to measure whether different… See the full description on the dataset page: https://huggingface.co/datasets/kishan51/llm-affect-lab.nla-affect-10k
NLA Affect 10k
Research dataset for supervised initialization of an affect-aware natural-language
autoencoder (NLA) for Qwen/Qwen2.5-7B-Instruct, using the raw output of
model.layers[20] at the final token (before final RMSNorm).
Contents
10,000 text prefixes: 9,000 general and 1,000 emotion-rich.
A 3,584-dimensional activation vector for each prefix.
Teacher explanations with <context>, <affect>, and <local> sections.
Scores from eight layer-20 linear emotion… See the full description on the dataset page: https://huggingface.co/datasets/MaxChess/nla-affect-10k.algocean-affect-router
algocean-affect-router
사용자 발화를 받아 지금 공감이 필요한지, 해결·정보가 필요한지 판정하도록 가르치는 LoRA SFT 데이터셋입니다.
사용자의 성격이 아니라 이 프롬프트가 지금 요구하는 응답 방식을 가르칩니다.
규모
파일
행 수
affect_router.jsonl
41,042
affect_router.eval.jsonl
2,000
형식: JSONL, messages 3턴
언어: 한국어 약 70% · 영어 약 30%
최소쌍(pair_id) 포함 — train/eval 분할 시 쌍 단위로 나눌 것
어디에 쓰나요
챗봇 응답 전 공감(F) vs 해결(T) 라우팅
같은 주제라도 어투에 따라 답이 달라져야 하는 경우
경량 모델로 톤 분기만 맡길 때
어떤 모델에 LoRA 하나요
출력이 짧고 클래스가 적어 가장 가벼운… See the full description on the dataset page: https://huggingface.co/datasets/Algocean/algocean-affect-router.rhvex-affects
Dataset Card for rhvex-affects
This Dataset is extracted from publicly available Vulnerability Exploitability eXchange (VEX) files published by Red Hat.
Dataset Details
Red Hat security data is a central source of truth for Red Hat products regarding published, known vulnerabilities.
This data is published in form of Vulnerability Exploitability eXchange (VEX) available at:
https://security.access.redhat.com/data/csaf/v2/vex/
This Dataset is created by extracting… See the full description on the dataset page: https://huggingface.co/datasets/vdanen/rhvex-affects.