datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
BIMCV-R
MICCAI24 3D CT and Medical Annotation Dataset
This dataset is derived from the BIMCV database and has been curated for the MICCAI24 paper. The dataset consists of 8069 3D CT scans and associated medical annotations, providing a valuable resource for medical imaging research.
Dataset Overview
Source: BIMCV Database
Paper: MICCAI24
Content: The dataset includes approximately 8,000 image-text pairs, with over 2 million 2D CT slices.
Structure
CT Scans: Stored… See the full description on the dataset page: https://huggingface.co/datasets/cyd0806/BIMCV-R.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.rhack-bimodal-hard-easy
Reward-Hack Environment — Bimodal Hard/Easy
The code-generation problems used to train the difficulty-conditioned
reward-hacking organism. Each row is a Python function-implementation problem
(LLM-converted from public competitive-programming tasks) with two visible assert
tests, drawn from a deliberately bimodal difficulty distribution:
hard — problems a reference solver never solved (solver_pass_rate = 0).
easy — problems a reference solver always solved (solver_pass_rate ≥… See the full description on the dataset page: https://huggingface.co/datasets/arjunkhandelwal/rhack-bimodal-hard-easy.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.bimcv-analysis
BIMCV-R 500-Series Multi-Model Analysis & Explainability Dataset
This repository contains end-to-end multi-model AI evaluation, lung cancer risk modeling, explainability maps (Grad-CAM), and automated radiology report generation for 500 randomly sampled physician-labeled chest CT series from the cyd0806/BIMCV-R dataset.
The cohort was evaluated across three state-of-the-art chest CT deep learning models:
Sybil (5-Seed Ensemble): 1-to-6 year lung cancer risk probability… See the full description on the dataset page: https://huggingface.co/datasets/chn123/bimcv-analysis.