s1
Models
All models matching “s1”CLIP-convnext_base_w-laion2B-s13B-b82K-augregCLIP-ViT-B-16-DataComp.XL-s13B-b90Ks1-mini-GGUFCLIP-ViT-B-32-xlm-roberta-base-laion5B-s13B-b90kCLIP-convnext_base_w_320-laion_aesthetic-s13B-b82K-augregMobileCLIP-S1-OpenCLIPCLIP-ViT-L-14-DataComp.XL-s13B-b90KCLIP-ViT-H-14-frozen-xlm-roberta-large-laion5B-s13B-b90k
Datasets
All datasets matching “s1”Core-S1RTC
Core-S1RTC
Contains a global coverage of Sentinel-1 (RTC) patches, each of size 1,068 x 1,068 pixels.
Source
Sensing Type
Number of Patches
Patch Size
Total Pixels
Sentinel-1 RTC
Synthetic Aperture Radar
1,469,955
1,068 x 1,068 (10 m)
> 1.676 Trillion
Content
Column
Details
Resolution
VV
Received Linear Power in the VV Polarization
10m
VH
Received Linear Power in the VV Polarization
10m
thumbnail
Rescaled false colour1 saved as png
10m1… See the full description on the dataset page: https://huggingface.co/datasets/Major-TOM/Core-S1RTC.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.leaague-of-legends-decoded-replay-packets-s12-unorganized
Disclaimer
This work isn’t endorsed by Riot Games and doesn’t reflect the views or opinions of Riot Games or anyone officially involved in producing or managing League of Legends. League of Legends and Riot Games are trademarks or registered trademarks of Riot Games, Inc.
Citation
If you use this dataset in your research, please cite:
@dataset{league_of_legends_decoded_replay_packets_2025,
title={League of Legends Decoded Replay Packets Dataset},
author={maknee}… See the full description on the dataset page: https://huggingface.co/datasets/maknee/leaague-of-legends-decoded-replay-packets-s12-unorganized.UrbanSARFloods_v1SSL4EO-S12-v1.1
SSL4EO-S12-v1.1
Attention: The Zarr Chunk file version of SSL4EO-S12-v1.1 was moved to embed2scale/SSL4EO-S12-v1.1-Zarr. This repository contains data that can be used with webdataset.
The dataset includes 246,144 locations with four timestamps each from the modalities S2L1C, S2L2A, S2RGB, S1GRD, LULC, DEM, and NDVI.
We refer to our technical report for details.
The samples are stored in as Zarr Zip files (zarr version 2) with the metadata directly aligned as additional data… See the full description on the dataset page: https://huggingface.co/datasets/embed2scale/SSL4EO-S12-v1.1.