s1k
Datasets
All datasets matching “s1k”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.s1K-1.1_tokenizeds1K-1.1
Dataset Card for s1k-1.1
This is a formatted version of the simplescaling/s1K-1.1 dataset to include a messages column that can be directly used within TRL. Please refer to the original dataset and paper for details.
s1K_tokenized
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_tokenized.simplescaling-s1K-R1
Dataset Card: s1k R1
Dataset Description
The s1k R1 dataset is a fork of the simplescaling/s1K dataset. It contains a collection of conversations where the assistant's messages have been enhanced to include Chain of Thought (CoT) reasoning within <think> ... </think> tags, followed by the final answer. This modification aims to improve the interpretability and reasoning capabilities of AI models by providing explicit thought processes in the responses.
Dataset… See the full description on the dataset page: https://huggingface.co/datasets/mkurman/simplescaling-s1K-R1.