datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
biology
CAMEL: Communicative Agents for “Mind” Exploration of Large Scale Language Model Society
Github: https://github.com/lightaime/camel
Website: https://www.camel-ai.org/
Arxiv Paper: https://arxiv.org/abs/2303.17760
Dataset Summary
Biology dataset is composed of 20K problem-solution pairs obtained using gpt-4. The dataset problem-solutions pairs generating from 25 biology topics, 25 subtopics for each topic and 32 problems for each "topic,subtopic" pairs.
We provide… See the full description on the dataset page: https://huggingface.co/datasets/camel-ai/biology.loong
Additional Information
Project Loong Dataset
This dataset is part of Project Loong, a collaborative effort to explore whether reasoning-capable models can bootstrap themselves from small, high-quality seed datasets.
Dataset Description
This comprehensive collection contains problems across multiple domains, each split is determined by the domain.
Available Domains:
Advanced Math
Advanced mathematics problems including calculus, algebra… See the full description on the dataset page: https://huggingface.co/datasets/camel-ai/loong.camel_ai_chemistry_instruction_datasetPathoROB-camelyon
PathoROB
Preprint | Code | Licenses | Cite
PathoROB is a benchmark for the robustness of pathology foundation models (FMs) to non-biological medical center differences.
PathoROB contains four datasets covering 28 biological classes from 34 medical centers and three metrics:
Robustness Index: Measures the dominance of biological over non-biological features in an FM representation space.
Average Performance Drop (APD): Measures the robustness of downstream models to shortcut… See the full description on the dataset page: https://huggingface.co/datasets/bifold-pathomics/PathoROB-camelyon.CAMELYON17
CAMELYON17
1. Tổng quan
CAMELYON17 là dataset mở rộng của CAMELYON16, gồm ảnh WSI hạch bạch huyết canh gác từ 5 trung tâm y tế khác nhau (multi-center), với 1000 WSI (5 slide/bệnh nhân x 200 bệnh nhân). Bài toán chính là phân loại di căn theo 4 mức tại cấp lymph-node (negative/isolated tumor cells/micro-metastases/macro-metastases) và tổng hợp thành pN-stage tại cấp bệnh nhân.
Nguồn dữ liệu: AWS Open Data, s3://camelyon-dataset/CAMELYON17/ (region us-west-2, truy… See the full description on the dataset page: https://huggingface.co/datasets/okbro1234/CAMELYON17.amc_aime_self_improving
Additional Information
This dataset contains mathematical problem-solving traces generated using the CAMEL framework. Each entry includes:
A mathematical problem statement
A detailed step-by-step solution
An improvement history showing how the solution was iteratively refined
Special thanks to our community contributor, GitHoobar, for developing the STaR pipeline!🙌
camel-componentsCAMEL-Benchoh_v1.2_sin_camel_biology_diversityoh_v1.2_sin_camel_biology_diversityBAREC-Corpus-v1.0
BAREC Corpus v1.0
Dataset Summary
BAREC (the Balanced Arabic Readability Evaluation Corpus) is a large-scale dataset for fine-grained Arabic readability assessment.
The dataset includes over 1M words, annotated at the sentence level across 19 readability levels, with additional mappings to coarser 7, 5, and 3 level schemes.
Supported Tasks
The dataset supports multi-class readability classification in the following formats:
19 levels (default)
7 levels
5… See the full description on the dataset page: https://huggingface.co/datasets/CAMeL-Lab/BAREC-Corpus-v1.0.camel-ai-physics
CAMEL: Communicative Agents for “Mind” Exploration of Large Scale Language Model Society
Github: https://github.com/lightaime/camel
Website: https://www.camel-ai.org/
Arxiv Paper: https://arxiv.org/abs/2303.17760
Dataset Summary
Physics dataset is composed of 20K problem-solution pairs obtained using gpt-4.
The dataset problem-solutions pairs generating from 25 physics topics, 25 subtopics for each topic and 32 problems for each "topic,subtopic" pairs.… See the full description on the dataset page: https://huggingface.co/datasets/lgaalves/camel-ai-physics.amc_aime_distilled
Additional Information
This dataset contains mathematical problem-solving traces generated using the CAMEL framework. Each entry includes:
A mathematical problem statement
A detailed step-by-step solution
camel-ai-chemistrycamelot-bench-dataset
camelot-bench Dataset
Full self-play records from a run of camelot-bench, a multi-agent LLM
benchmark built on the social-deduction game The Resistance: Avalon. Every game,
proposal, vote, quest, role guess, speech, and post-game reflection is included,
with the private reasoning behind each decision.
This dataset was generated by camelot-bench and is not affiliated with or endorsed
by the publisher of The Resistance: Avalon.
Run: 260911142213-0700
Games: 100 (5 players each)… See the full description on the dataset page: https://huggingface.co/datasets/zihyuan/camelot-bench-dataset.camel_ai_physics_instruction_datasetcamel-ai-biologycamel-ai-physicsgsm8k_distilled
Additional Information
This dataset contains mathematical problem-solving traces generated using the CAMEL framework. Each entry includes:
A mathematical problem statement
A detailed step-by-step solution
camelcamel_ai_biology_instruction_datasetcamel-bioFull_Agent_RL_OPSD_with_Just_2_A800scamel-languagescamel-eipscamel_ai_physics
Dataset Card for "camel_ai_physics"
More Information needed
BAREC-Shared-Task-2025-sent
BAREC Shared Task 2025
Dataset Summary
BAREC (the Balanced Arabic Readability Evaluation Corpus) is a large-scale dataset developed for the BAREC Shared Task 2025, focused on fine-grained Arabic readability assessment. The dataset includes over 1M words, annotated across 19 readability levels, with additional mappings to coarser 7, 5, and 3 level schemes.
The dataset is annotated at the sentence level. Document-level readability scores are derived by assigning each… See the full description on the dataset page: https://huggingface.co/datasets/CAMeL-Lab/BAREC-Shared-Task-2025-sent.wds_wilds-camelyon17_testOWL-SFT
OWL SFT (Planner) Dataset
Dataset Summary
OWL SFT is a supervised fine‑tuning dataset designed for training the planner agent in the Optimized Workforce Learning (OWL) framework – a system for multi‑agent assistance in real‑world task automation.
The dataset contains 1,564 multi‑turn conversations, focusing on task decomposition, sequencing, and coordination skills that are crucial for high‑level planning.
Languages
All conversation turns are written in… See the full description on the dataset page: https://huggingface.co/datasets/camel-ai/OWL-SFT.OH_DCFT_v1_wo_camel_chemistry_gpt-4o-mini