datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
omnimcp_browser_dom_structured_extractor_teaser
🔬 INSPECT THE DEEPSEEK-R1 REASONING CHAIN LIVE:
Zero hallucinations. Null syntax errors. 100% AST compiler validated.🌐 Live Interactive Reasoning & Code Inspector: https://emgena.com/trainingslager🎁 Claim your Free Starter Kit (Code: STARTER100): https://emgena.com/trainingslager🏷️ Launch Discount: Get 20 € OFF any 500-incident production suite with code LAUNCH20!
📜 Enterprise Compliance: EU AI Act Articles 50 & 53 certified • 100% DSGVO / GDPR clean • Commercial EULA… See the full description on the dataset page: https://huggingface.co/datasets/emgena/omnimcp_browser_dom_structured_extractor_teaser.omnimcp_graphrag_triplet_extractor_teaser
🔬 INSPECT THE DEEPSEEK-R1 REASONING CHAIN LIVE:
Zero hallucinations. Null syntax errors. 100% AST compiler validated.🌐 Live Interactive Reasoning & Code Inspector: https://emgena.com/trainingslager🎁 Claim your Free Starter Kit (Code: STARTER100): https://emgena.com/trainingslager🏷️ Launch Discount: Get 20 € OFF any 500-incident production suite with code LAUNCH20!
📜 Enterprise Compliance: EU AI Act Articles 50 & 53 certified • 100% DSGVO / GDPR clean • Commercial EULA… See the full description on the dataset page: https://huggingface.co/datasets/emgena/omnimcp_graphrag_triplet_extractor_teaser.omnimcp_episodic_fact_extractor_teaser
🔬 INSPECT THE DEEPSEEK-R1 REASONING CHAIN LIVE:
Zero hallucinations. Null syntax errors. 100% AST compiler validated.🌐 Live Interactive Reasoning & Code Inspector: https://emgena.com/trainingslager🎁 Claim your Free Starter Kit (Code: STARTER100): https://emgena.com/trainingslager🏷️ Launch Discount: Get 20 € OFF any 500-incident production suite with code LAUNCH20!
📜 Enterprise Compliance: EU AI Act Articles 50 & 53 certified • 100% DSGVO / GDPR clean • Commercial EULA… See the full description on the dataset page: https://huggingface.co/datasets/emgena/omnimcp_episodic_fact_extractor_teaser.algocean-extractor
algocean-extractor
질의와 문서 묶음을 받아 답의 근거 span을 원문 그대로 뽑거나, 없으면 기권하도록 가르치는 LoRA SFT 데이터셋입니다.
RAG / 사내 QA 파이프라인의 근거 추출 노드용입니다. 답을 쓰지 않고, 재료가 어디에 있는지만 가리킵니다.
규모
파일
행 수
extractor.jsonl
150,000
extractor.eval.jsonl
2,000
형식: JSONL, messages 3턴 (system / user / assistant)
언어: 한국어 약 70% · 영어 약 30%
eval은 학습셋과 별도 생성
어디에 쓰나요
문서 청크에서 문자 단위 근거 인용이 필요한 추출기
“모르면 기권” 정책을 경량 모델에 LoRA로 심을 때
프론티어 모델 앞단의 값싼 grounding 필터
어떤 모델에 LoRA 하나요… See the full description on the dataset page: https://huggingface.co/datasets/Algocean/algocean-extractor.