long-cot
MathSmith-Qwen3-8B-LongCoT-i1-GGUFlongnav-objectnav-flow-nopose-cotrain-2p5hz-mergedMathSmith-DS-Qwen-7B-LongCoT-i1-GGUFOpenBuddy-R10528DistillQwen-14B-v27.2-LongCoTRL-i1-GGUFDemeter-LongCoT-Qwen3-1.7B-GGUFDemeter-LongCoT-Qwen3-1.7B-i1-GGUFMistral-Large-2407-LongCoT-i1-GGUFDemeter-LongCoT-Qwen3-1.7B-GGUF
Datasets
All datasets matching “long-cot”Demeter-LongCoT-6M
Demeter-LongCoT-6M
Demeter-LongCoT-6M is a high-quality, compact chain-of-thought reasoning dataset curated for tasks in mathematics, science, and coding. While the dataset spans diverse domains, it is primarily driven by mathematical reasoning, reflecting a major share of math-focused prompts and long-form logical solutions.
Quick Start with Hugging Face Datasets🤗
pip install -U datasets
from datasets import load_dataset
dataset =… See the full description on the dataset page: https://huggingface.co/datasets/prithivMLmods/Demeter-LongCoT-6M.AIME_MATH_1000_LONG_COTlongcot
LongCoT
LongCoT is a benchmark for long-horizon reasoning across logic, computer science, chemistry, chess, and mathematics. This Hugging Face release contains the benchmark data in viewer-friendly Parquet format for browsing and loading with datasets.
The canonical codebase, verifier, and evaluation harness live at:
https://github.com/LongHorizonReasoning/longcot
Overview
LongCoT measures whether models can sustain coherent reasoning across long chains of thought. The… See the full description on the dataset page: https://huggingface.co/datasets/LongHorizonReasoning/longcot.QwQ-LongCoT-130KAlso have a look on the second version here => QwQ-LongCoT-2
Figure 1: Just a cute picture generate with [Flux](https://huggingface.co/Shakker-Labs/FLUX.1-dev-LoRA-Logo-Design)
Today, I’m excited to release QwQ-LongCoT-130K, a SFT dataset designed for training O1-like large language models (LLMs). This dataset includes about 130k instances, each with responses generated using QwQ-32B-Preview. The dataset is available under the Apache 2.0 license, so feel free to use it as you like.… See the full description on the dataset page: https://huggingface.co/datasets/amphora/QwQ-LongCoT-130K.LONGCOT-merged-1Mthis is PowerInfer/QWQ-LONGCOT-500K + PowerInfer/LONGCOT-Refine-500K shuffled together with the following changes:
pointless starting phrases at the beginning (in english) such as "Okay, ..." "So, ..." etc are removed
config en has been filtered to include only rows detected as lang en in both prompt and response columns via fasttext
QwQ-LongCoT-Verified-130KOriginal Dataset: amphora/QwQ-LongCoT-130K
QwQ 32B Preview isn't perfect :)
Note: Around 5-7% of the processed data might be incorrectly labeled as "unverified" because QwQ's output isn't exactly the same as the original solution from NuminaMathCoT. I believe this can be solved with another round of processing with a smarter model but Qwen 2.5 3B Instruct is good enough to check if the solution is exactly the same. Magpie data is also "unverified" and has an empty "solution" column.… See the full description on the dataset page: https://huggingface.co/datasets/qingy2024/QwQ-LongCoT-Verified-130K.