datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Math_CoT_Arabic_English_Reasoning
Math CoT Arabic English Dataset
A high-quality, bilingual (English & Arabic) dataset for Chain-of-Thought (COT) reasoning in mathematics and related disciplines, developed by Miscovery AI.
Overview
Math-COT is a unique dataset designed to facilitate and benchmark the development of chain-of-thought reasoning capabilities in language models across mathematical domains. With meticulously crafted examples, explicit reasoning steps, and bilingual support, this dataset offers… See the full description on the dataset page: https://huggingface.co/datasets/miscovery/Math_CoT_Arabic_English_Reasoning.easy_turkish_math_reasoning
Easy Turkish Math Reasoning
Dataset Summary
The Easy Turkish Math Reasoning dataset is the first phase of a multi-stage curriculum learning pipeline designed to enhance the reasoning abilities of compact language models. This dataset focuses on elementary-level arithmetic and logic problems in Turkish, serving as a warm-up stage for supervised fine-tuning (SFT).
Use Case
Primarily used for:
Bootstrapping reasoning ability in Turkish for compact LLMs.
Phase 1… See the full description on the dataset page: https://huggingface.co/datasets/erayalp/easy_turkish_math_reasoning.medium_turkish_math_reasoning
Dataset Summary
The Medium Turkish Math Reasoning dataset is Phase 2 of a curriculum learning pipeline to teach compact models multi-step reasoning in Turkish. It includes moderately difficult math problems involving multiple reasoning steps, such as two-part arithmetic, comparisons, and logical reasoning.
Use Case
This dataset is ideal for:
Continuing SFT after foundational training with simpler problems.
Bridging the gap between basic arithmetic and complex GSM8K-style… See the full description on the dataset page: https://huggingface.co/datasets/erayalp/medium_turkish_math_reasoning.