datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
enterprise_erp_workflow_reasoning
Enterprise ERP Workflow Reasoning
Author: Venkata Ramachandra Karthik Chundi (venkatakarthikchundi@gmail.com)
A multiple-choice benchmark testing LLM reasoning on enterprise ERP business process workflows, approval hierarchies, document relationships, and process sequencing. Scenarios are drawn from real-world Oracle ERP Cloud deployment contexts.
Dataset
50 multiple-choice questions with 4 answer options each. One correct answer per question.
Modules Covered… See the full description on the dataset page: https://huggingface.co/datasets/karthikchundi/enterprise_erp_workflow_reasoning.erpbench-distribution
ERPBench Distribution
An execution-graded text-to-T-SQL benchmark for wholesale distribution ERP. Every gold query has been verified by double execution against a live SQL Server 2022 instance, and the grading harness that produced our published numbers ships in this repo, so results are reproducible from a clean checkout.
Most text-to-SQL benchmarks grade string similarity or run against toy schemas. Real ERP work means 60-table schemas, money columns, date arithmetic… See the full description on the dataset page: https://huggingface.co/datasets/Lumina-ERP/erpbench-distribution.saas-erp-support-ru-train-v13
Capstone support: F training shards
Train-only synthetic Russian SaaS / fictional ERP / telecom scenarios:
430 dialogues, 1113 target turns, 13 local JSONL shards. No real company or customer data.
No validation/test split is published here. Files preserve project-relative paths
under data/quality90_v1/train; restore those paths in a checkout to reuse them.
Each dialogue contains context and turn-level target labels/replies. The exact
file list and SHA-256 hashes are in… See the full description on the dataset page: https://huggingface.co/datasets/AkanaYB/saas-erp-support-ru-train-v13.ERP-RP-EVISCERATED-PATCHERThis is a small dataset with some of the RP/RP and Math problems.
I am wanting another domain (In this case, math problems) to help patch my scooped (I.E EVISCERATED) models.
Deepseek-R1-ERP-DatasetDataset ERP dataset generated from deepseek R1. This was a bit intensive. I write a python scrip that would generate a random plot, the ERP theme of which was chosing at random from about 20 different types of themes (One of the more tame ones, for example, "Romance Erotica"). I would then guide the inference by using the "user" role to switch perspectives between the two characters, and continue the story.
I then wrote another script that used deepseek-cat to fix the reasoning portions.… See the full description on the dataset page: https://huggingface.co/datasets/SuperbEmphasis/Deepseek-R1-ERP-Dataset.Deepseek-R1-Reasoning-ERP-Limiter-TestThis is an experiment. For RP, sometimes the thinking that Deepseek and others do are a bit much. Since I Now have a rather large (ish) deepseek R1 dataset. I made a python script to count the number of words from the reasoning, round up to the nearest 50 (So if the number was 416, this would be set to 450), and then add some text in the system prompt and the reasoning.
My goal is to easily, via a system prompt, be able to control the size/amount of tokens from thinking.
Claude-Deepseek-R1-ERP-RP-REASONING-AND-NONREASONING-DatasetER-PRM-Datalima-erp
长对话数据的拷贝，使用google翻译了部分数据
数据格式符合llama-factory
oracle-erp-workflow-eval
Oracle ERP Cloud Workflow & Terminology Eval
A benchmark dataset for evaluating large language models on Oracle ERP Cloud knowledge — including workflows, terminology, document types, approval hierarchies, and process flows across seven core Oracle Cloud modules.
Overview
Property
Value
Samples
30
Modules covered
7
Task type
Short-answer question answering
Eval framework
OpenAI Evals (FuzzyMatch)
Metric
Accuracy (fuzzy string match)… See the full description on the dataset page: https://huggingface.co/datasets/karthikchundi/oracle-erp-workflow-eval.Orion-LIMA-ERPERPNexterp100_chERP_DATASETyoungkklerperp_distill