simp
vitpose-base-simpleQwen3.8-27B-EfficientThink-Uncensored-K3-Opus5-Grok4.6-GPT5.6Sol-SFT-SimPO-DFlash2-GGUFQwen3.8-27B-EfficientThink-Uncensored-K3-Opus5-Grok4.6-GPT5.6Sol-SFT-SimPO-DFlash2chatgpt-detector-robertaSimpleStories-V2-1.25MLlama-3-Instruct-8B-SimPO-SPPO-Iter3-mergeLlama-3-Instruct-8B-CPO-SimPOLlama-3-Instruct-8B-SPPO-Iter3-SimPO-merge
Datasets
All datasets matching “simp”HiFi-UMI-2K
HiFi-UMI-2K: High-Fidelity Robot-Free Manipulation Data
2,000 hours released · 6 synchronized camera views · 480+ scenes · 3 mm pose accuracy · <40 µs synchronization
🌐 Project Website |
📦 Dataset |
📄 Paper: arXiv:2607.25895
Examples from the HiFi-UMI corpus. Click the image to play the video.
📚 Introduction
HiFi-UMI is a portable, high-fidelity bimanual capture system for collecting robot-free manipulation demonstrations.… See the full description on the dataset page: https://huggingface.co/datasets/simple-world-lab/HiFi-UMI-2K.simplipy-assets
simplipy assets
Rule sets and engine configurations for simplipy,
a fast, contract-sound simplification engine for symbolic mathematical expressions.
The engine and these rule sets are described in: Saegert & Köthe 2026, Breaking the
Simplification Bottleneck in Amortized Neural Symbolic Regression (ICML 2026),
arXiv:2602.08885.
Install an engine by name (downloads this repository's files on first use):
pip install simplipy
import simplipy as sp
engine =… See the full description on the dataset page: https://huggingface.co/datasets/psaegert/simplipy-assets.s1K-1.1
Dataset Card for s1K
Dataset Summary
s1K-1.1 consists of the same 1,000 questions as in s1K but with traces instead generated by DeepSeek r1. We find that these traces lead to much better performance.
Usage
# pip install -q datasets
from datasets import load_dataset
ds = load_dataset("simplescaling/s1K-1.1")["train"]
ds[0]
Dataset Structure
Data Instances
An example looks as follows:
{
'solution': '1. **Rewrite the function using… See the full description on the dataset page: https://huggingface.co/datasets/simplescaling/s1K-1.1.s1K
Dataset Card for s1K
Dataset Summary
s1K is a dataset of 1,000 examples of diverse, high-quality & difficult questions with distilled reasoning traces & solutions from Gemini Thining. Refer to the s1 paper for more details.
Usage
# pip install -q datasets
from datasets import load_dataset
ds = load_dataset("simplescaling/s1K")["train"]
ds[0]
Dataset Structure
Data Instances
An example looks as follows:
{
'solution': '1. **Rewrite… See the full description on the dataset page: https://huggingface.co/datasets/simplescaling/s1K.aime24_nofiguresThe 30 problems from AIME 2024 only with the ASY code for figures when it is necessary to solve the problem. Figure code that is not core to the problem was excluded.
Citation Information
@misc{muennighoff2025s1simpletesttimescaling,
title={s1: Simple test-time scaling},
author={Niklas Muennighoff and Zitong Yang and Weijia Shi and Xiang Lisa Li and Li Fei-Fei and Hannaneh Hajishirzi and Luke Zettlemoyer and Percy Liang and Emmanuel Candès and Tatsunori Hashimoto}… See the full description on the dataset page: https://huggingface.co/datasets/simplescaling/aime24_nofigures.SimpleRL-Zoo-Data