code-reasoning
Code-Reasoning
Code-Reasoning
Dataset Description
Code problem-solving data with reasoning, direct-answer, and task-synthesis subsets. This repository is part of the K2 Horizon collection.
The repository is organized into multiple subsets. Every subset has a train split backed by Parquet shards, which supports Dataset Viewer inspection and streaming access.
K2 Horizon Dataset Series
Dataset repository
Focus
Subsets
IFM/TxT360-v2
Web and… See the full description on the dataset page: https://huggingface.co/datasets/IFM/Code-Reasoning.verifiable-code-reasoning
Verifiable Code Reasoning
Execution-verified Python problems with chain-of-thought
Sandbox-checked solutions · Multi-test unit checks · Deduplicated instances · Training-ready sft_text
Overview
Verifiable Code Reasoning is a large-scale dataset of Python coding problems where every kept solution has passed sandboxed unit tests.
Unlike scraped contest dumps or unverified LLM traces, an example enters this release only if:
a reference… See the full description on the dataset page: https://huggingface.co/datasets/smshahbaj/verifiable-code-reasoning.Code-Reasoning
Code-Reasoning
Dataset Description
Code problem-solving data with reasoning, direct-answer, and task-synthesis subsets. This repository is part of the K2 Horizon collection.
The repository is organized into multiple subsets. Every subset has a train split backed by Parquet shards, which supports Dataset Viewer inspection and streaming access.
K2 Horizon Dataset Series
Dataset repository
Focus
Subsets
IFM/TxT360-v2
Web and… See the full description on the dataset page: https://huggingface.co/datasets/LexyJawa/Code-Reasoning.NOESIS-1M-reasoning-router-code-math-psych-opus47-deepseek4-qwen36-gemini31-r1-gpt54
⚡ Each donation funds the next large quant.
I host free GGUF or MoE quants as independent research.
Local hardware: Mechrevo Kuangshi GM7AG0M — RTX 3060 Laptop 6GB GDDR6, 64GB DDR5, i7-12700H (14C/20T, 4.7GHz), Windows 11, Samsung 990 Pro.
Good for imatrix and 0.6–35B-class work in RAM. 9B+ and searches need rented H200/Blackwell, typically $100 per quant.
🎉 Boosty🦄 |
☕ Buy Me a Coffee🦄 |
⭐ DonationAlerts🦄
💚 Thanks to Hugging Face for extra storage.🦄… See the full description on the dataset page: https://huggingface.co/datasets/AMAImedia/NOESIS-1M-reasoning-router-code-math-psych-opus47-deepseek4-qwen36-gemini31-r1-gpt54.Z1-Code-Reasoning-107K
Z1: Efficient Test-time Scaling with Code
Train Large Language Model to Reason with Shifted Thinking
[📜 Paper] •
[🤗 HF Models] •
[🐱 GitHub]
Details
Please refer to https://github.com/efficientscaling/Z1.
Usage
from datasets import load_dataset
ds = load_dataset("efficientscaling/Z1-Code-Reasoning-107K")["train"]
ds[0]
Citation
@misc{yu2025efficientscaling,
title={Z1: Efficient Test-time Scaling with Code}… See the full description on the dataset page: https://huggingface.co/datasets/efficientscaling/Z1-Code-Reasoning-107K.NOESIS-50K-reasoning-router-code-math-psych-opus47-deepseek4-qwen36-gemini31-r1-gpt54
⚡ Each donation funds the next large quant.
I host free GGUF or MoE quants as independent research.
Local hardware: Mechrevo Kuangshi GM7AG0M — RTX 3060 Laptop 6GB GDDR6, 64GB DDR5, i7-12700H (14C/20T, 4.7GHz), Windows 11, Samsung 990 Pro.
Good for imatrix and 0.6–35B-class work in RAM. 9B+ and searches need rented H200/Blackwell, typically $100 per quant.
🎉 Boosty🦄 |
☕ Buy Me a Coffee🦄 |
⭐ DonationAlerts🦄
💚 Thanks to Hugging Face for extra storage.🦄… See the full description on the dataset page: https://huggingface.co/datasets/AMAImedia/NOESIS-50K-reasoning-router-code-math-psych-opus47-deepseek4-qwen36-gemini31-r1-gpt54.