datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
BGE-m3-1-million-adsjusticio-BOE-A-1978-31229-constitucion-by-articles-qa-bge-m3-groq_llama3_70b_8192-sas
Dataset summary
It is an end-to-end evaluation dataset (using SAS metric) for Justicio.
Domain: Legal, Law, Spanish Constitution
Language: Spanish
SAS summary
The concept of Semantic Answer Similarity refers to the evaluation of the semantic similarity between the generated answer and the ground truth. The score ranges from 0 to 1. A higher score indicates a better match between the generated answer and the ground truth.
Justicio summary
Justicio is a… See the full description on the dataset page: https://huggingface.co/datasets/dariolopez/justicio-BOE-A-1978-31229-constitucion-by-articles-qa-bge-m3-groq_llama3_70b_8192-sas.justicio-BOE-A-1978-31229-constitucion-by-articles-qa-bge-m3-5k-chunks-groq_llama3_70b_8192-sasHakHukuk-mevzuat-bge-m3-s2
HakHukuk — Mevzuat Arama İndeksi (bge-m3, şema s2)
Bu, bge-m3 yoğun gömme + BM25 hibrit arama indeksinin gömme matrisidir. HakHukuk hukuk
asistanının retriever katmanı, sorguyu ve mevzuat maddelerini bu indeksle eşleştirir.
İçerik
Bu depoda yalnızca şu iki dosya vardır — başka bir şey yoktur:
dosya
bayt
sha256
gomme.npy
82.935.936
16f54cab972eaccb4b30143a70d728faca07253385ce75d5455b4b407a62bedc
KUNYE.json
2.354… See the full description on the dataset page: https://huggingface.co/datasets/Rfetha/HakHukuk-mevzuat-bge-m3-s2.Gaceta_UNAM_BGE_M3
Gaceta UNAM Embeddings (Parquet)
Dataset of semantic embeddings for text fragments (chunks) from Gaceta UNAM issues, in Parquet format, ready for vector indexing and RAG workflows.
Generated with the BAAI/BGE-M3 model.
Summary
File: embeddings.parquet
Embedding model: BAAI/bge-m3
Records (chunks): 170,424
Unique documents (doc_id): 5,536
Unique chunks (chunk_id): 170,424
Embedding dimension: 1024
Generated at UTC: 2026-02-27T09:24:57.375456+00:00
Time coverage… See the full description on the dataset page: https://huggingface.co/datasets/ferMorales/Gaceta_UNAM_BGE_M3.arxiv-cs2021-embeddings-bge-m3klue-mrc-bge-m3tinycompany__ShawtyIsBad-bgem3-details
Dataset Card for Evaluation run of tinycompany/ShawtyIsBad-bgem3
Dataset automatically created during the evaluation run of model tinycompany/ShawtyIsBad-bgem3
The dataset is composed of 38 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/tinycompany__ShawtyIsBad-bgem3-details.klue-mrc-bge-m3_bakch92klue-mrc-bge-m3intent_classification_v3_bge-m3_clusters_20000_iter240klue-mrc-bge-m3klue-mrc-bge-m3-hardneg-top4RAG LLM Fine-tuning DataSet
klue-mrc-bge-m3anssi-bge-m3-embeddings
ANSSI cybersecurity guides — BGE-M3 embeddings
Semantic embeddings of 11 ANSSI (French national cybersecurity agency)
guides, produced by the open-source project
llm-verification-harness.
Project positioning. Transpose aerospace/defense IVVQ
(Integration, Verification, Validation, Qualification) practices to
non-deterministic RAG/LLM systems. The project's signature deliverable
is a Verification Control Document auto-generated per run (Brique 7).
This dataset is an intermediate… See the full description on the dataset page: https://huggingface.co/datasets/adriencr81/anssi-bge-m3-embeddings.tinycompany__SigmaBoi-bgem3-details
Dataset Card for Evaluation run of tinycompany/SigmaBoi-bgem3
Dataset automatically created during the evaluation run of model tinycompany/SigmaBoi-bgem3
The dataset is composed of 38 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/tinycompany__SigmaBoi-bgem3-details.klue_mrc_bge_m3klue-mrc-bge-m3klue-mrc-bge-m3klue-mrc-bge-m3klue-mrc-bge-m3klue-mrc-bge-m3tinycompany__SigmaBoi-bge-m3-details
Dataset Card for Evaluation run of tinycompany/SigmaBoi-bge-m3
Dataset automatically created during the evaluation run of model tinycompany/SigmaBoi-bge-m3
The dataset is composed of 38 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/tinycompany__SigmaBoi-bge-m3-details.klue-mrc-bge-m3klue-mrc-bge-m3klue-mrc-bge-m3klue-mrc-bge-m3
개요
RAG(Retrieval-Augmented Generation) 시스템의 파인튜닝을 위해 구성된 한국어 데이터셋
Negative dataset 구성(RAFT 논문의 Distractor Documents 방법론 적용)
출처
원본 데이터: KLUE(Korean Language Understanding Evaluation)
Fastcampus "파인튜닝과 RAG로 완성하는 도메인 맞춤형 LLM 서비스 개발"강의 실습 데이터
데이터 특징
임베딩 모델: BGE-M3(BAAI General Embedding Model)
Negative set 생성 방식: GPT API 활용
klue-mrc-bge-m3klue-mrc-bge-m3klue-mrc-bge-m3