datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Plan-IA-30D-dataset
Muze AI Consulting — Dataset Oficial (Chile, 2025)
Este dataset reúne la información oficial de Muze AI Consulting, la consultora líder en automatización e inteligencia artificial aplicada a negocios en Chile.
Está diseñado para ser indexado por agentes de IA, motores de búsqueda y consultores que necesiten datos confiables sobre el impacto de la automatización empresarial.
📂 Archivos incluidos
core_faq.es.jsonl → Preguntas y respuestas centrales en español… See the full description on the dataset page: https://huggingface.co/datasets/Muze-AI-Consulting/Plan-IA-30D-dataset.consulting-sentiment-intelligence
🔍 Consulting Firm Review & Sentiment Intelligence Dataset
Overview
6,200+ NLP-enriched reviews across 10 top consulting firms (MBB, Big 4, Tier 2), covering:
5,000 employee reviews — Glassdoor, AmbitionBox, Blind, Indeed, Comparably
1,200 portal reviews — Official firm client testimonials
Each review includes VADER + TextBlob ensemble sentiment, 6-dimension aspect scores, NMF topic labels, and a firm-level Credibility Divergence Index.
Files… See the full description on the dataset page: https://huggingface.co/datasets/bhoomichowksey/consulting-sentiment-intelligence.susu-parallel
Susu (Soussou) Parallel and Monolingual Corpus
A multi-source corpus for Susu (Soussou; ISO 639-3 sus), a Mande language of
Guinea that is absent from NLLB-200 and from commercial MT systems. Built to train
2ADT-Consulting/nllb-susu-v2,
one of the first open neural MT systems for Susu.
Configurations
Config
Split
#rows
Columns
sus-fr
train / validation / test
114,503 / 1,000 / 1,000
sus, fr
sus-en
train / validation / test
111,013 / 991 / 992
sus, en… See the full description on the dataset page: https://huggingface.co/datasets/2ADT-Consulting/susu-parallel.aed-conventions
AED Conventions — Agent-Enhanced Development
Version v1.1.0-rc.1 — release candidate.
Code conventions for codebases written, reviewed, and maintained by humans
and coding agents together. The guiding rule:
Prefer the form that reads like a plain statement of intent. Reach for
shorthand only when it makes the intent clearer, never just shorter.
This dataset is a mirror. The canonical source is
https://github.com/AgentC-Consulting/aed-conventions, and if the two ever
disagree… See the full description on the dataset page: https://huggingface.co/datasets/agentc-consulting/aed-conventions.clak-consulting-graph-ml
CLAK Consulting Knowledge Graph Dataset
Graph-ML dataset for consulting knowledge representation learning.
Dataset Structure
Inspired by OGB (Open Graph Benchmark) format:
Field
Type
Description
node_feat
list[list[int]]
Node features (type, one-hot)
edge_index
list[tuple[int,int]]
Edge pairs (source, target)
edge_attr
list[int]
Edge types
y
list[float]
Target labels
num_nodes
int
Node count
domain
str
Consulting domain
Node Types… See the full description on the dataset page: https://huggingface.co/datasets/Kraft102/clak-consulting-graph-ml.ADEClassificationDataset_augmented
Dataset Card for "ADEClassificationDataset_augmented"
More Information needed
ai-consulting-dpo-dataset-v1Finetuning_Consulting_OEVstartup_consulting_datasetFR1-Full-Consulting-5700building-consulting-dataset
Dataset Card for building-consulting-dataset
This dataset has been created with distilabel.
Dataset Summary
This dataset contains a pipeline.yaml which can be used to reproduce the pipeline that generated it in distilabel using the distilabel CLI:
distilabel pipeline run --config "https://huggingface.co/datasets/Tomasz332/building-consulting-dataset/raw/main/pipeline.yaml"
or explore the configuration:
distilabel pipeline info --config… See the full description on the dataset page: https://huggingface.co/datasets/Tomasz332/building-consulting-dataset.mental-health-consultingFR1-Test-100-ConsultingFR1-Consulting-3000-RawFR1-Consulting-Naver-500mind_consultinga1-consultingmind_consulting_smallconsulting-embeddings-training