datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
ifc-bim-qa-dataset
IFC BIM Question-Answering Dataset
A comprehensive question-answering dataset for Building Information Modeling (BIM) and Industry Foundation Classes (IFC) domain knowledge.
Dataset Summary
This dataset contains 13,485 question-answer pairs covering comprehensive BIM domain knowledge:
IFC Schema Knowledge: Entities, constraints, functions, and global rules
IFC Documentation: Specifications, concepts, geometry, and processes
Professional Certification: BIM practices… See the full description on the dataset page: https://huggingface.co/datasets/Dietmar2020/ifc-bim-qa-dataset.ifc-bim-alpaca-124k
IFC BIM Alpaca Dataset
Dataset Description
This dataset contains 124974 high-quality instruction-following examples for IFC (Industry Foundation Classes) and BIM (Building Information Modeling) in the Alpaca format. It covers IFC 4.3.x-devel standard entities, properties, relationships, and best practices.
Dataset Summary
Total Examples: 124974
Train Set: 112476 examples
Validation Set: 12498 examples
Language: English
Format: Alpaca (instruction, input… See the full description on the dataset page: https://huggingface.co/datasets/Dietmar2020/ifc-bim-alpaca-124k.ifc-bim-high-quality-alpaca
IFC BIM High-Quality Dataset (Alpaca Format)
Dataset Description
This is a high-quality, curated dataset for training language models on IFC (Industry Foundation Classes) and BIM (Building Information Modeling) tasks. The dataset has been filtered for quality and is provided in the Alpaca instruction-following format.
Dataset Summary
Total entries: 42,680
Format: Alpaca (instruction, input, output)
Language: English
Domain: IFC/BIM technical documentation and… See the full description on the dataset page: https://huggingface.co/datasets/Dietmar2020/ifc-bim-high-quality-alpaca.ifc-bim-gemma3-subset-1k
IFC-BIM Gemma3 Training Subset (1K Examples)
A 1,000-example subset of IFC/BIM Q&A data formatted for Gemma-3 fine-tuning with Unsloth.
Quick Start
from datasets import load_dataset
# Load dataset
dataset = load_dataset("your-username/ifc-bim-gemma3-subset-1k")
# View first example
print(dataset["train"][0])
Dataset Structure
ShareGPT format with quality scores:
conversations: List of human/gpt exchanges
source: Data origin
score: Quality rating… See the full description on the dataset page: https://huggingface.co/datasets/Dietmar2020/ifc-bim-gemma3-subset-1k.RAG_diet
Dataset Card for Dataset Name
RAG FOR DIETS
Dataset Details
Dataset Description
THIS IS A DATASET CREATED BY SLECTIVELY CHOOSING AND MERGING MULTIPLE DATASETS FROM VARIOUS SOURCERS INCLUDING OTHER DATASETS AND GENERATED
DATASETS.
FEEL FREE TO USE THESE ANYWHERE AND MAKE SURE TO CREDIT THE APPROPIATE DATA SOURCERS WHEREVER NECESSARY!!
😀
Curated by: [Navaneeth. K]